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Im August: LEGO erfüllt Fans einen großen Wunsch

Sun, 26 Jul 2026 12:45:15 +0200

LEGO erweitert seine Ideas-Reihe um ein neues Lizenz-Set, das viele Erinnerungen an die große Mystery-Ära der 90er weckt. Dieser Artikel wurde einsortiert unter Gaming, Lego.

EA Sports: Wer FC 27 für die PS4 ordert, erlebt eine Überraschung

Sun, 26 Jul 2026 12:45:14 +0200

Wer sich nach dem Trailer auf EA Sports FC 27 auf seiner PS4 freut, erwartet womöglich ein böses Erwachen. Im Kleingedruckten erwähnt EA, dass einige Features nicht enthalten sein werden. Dieser Artikel wurde einsortiert unter Gaming, Videospiel, EA Sports FC 27.

John Robertson's The Dark Room (emf2026)

Sun, 26 Jul 2026 12:05:29 +0200

Welcome to John Robertson’s THE DARK ROOM – the legendary interactive comedy show that fuses improv, crowdwork and gaming to create an insane live-action videogame! “An hilarious, participatory cult classic” Neil Patrick Harris “hilarious game show” Independent ★★★★ “A Rocky Horror for nerds… reader, I howled” Telegraph, London Come watch, and if you want – play – the choose-your-own-adventure madness! The crowd is trapped inside an inescapable dungeon with a sadistic videogame boss! Pick increasingly surreal options off the screen and try to escape! If you win – you get money! If you fail – YA DIE! YA DIE! YA DIE! Now, will you: Find the Light Switch Go North? Abandon Hope? Be sworn at by a man wearing spiked armour and a lot of leather? (This option is permanently set to “On”) Now in its 14th year, this high-octane interactive show is the brainchild of comedian & cult leader John Robertson. Filled with stand-up, appalling prizes and more audience chanting than you’d get at a protest – The Dark Room is a gut-busting comedy experience for everyone. Licensed to the public under https://creativecommons.org/licenses/by-sa/4.0/ about this event: https://www.emfcamp.org/schedule/2026/174-john-robertsons-the-dark-room

Microsoft will endlich Download-Probleme der Xbox beheben

Sun, 26 Jul 2026 12:01:07 +0200

Schwankende Raten, überlastete Server und eingefrorene Updates plagen oft Xbox-Nutzer. Microsoft greift nun mit einem smarten Download-Client ein. Das System wechselt die Route dynamisch und beschleunigt so die Installation neuer Titel. (Weiter lesen)

Gaming-Monster mit 4K-Mini-LED, RTX 5090 und 128 GB RAM – Asus ROG Strix SCAR 18 G835LXG im Test

Sun, 26 Jul 2026 10:30:15 +0200

Premium-Gaming mit kompromissloser Performance. | Asus aktualisiert sein ROG Strix SCAR 18 G835LXG mit dem Intel Core Ultra 9 290HX, einer Nvidia GeForce RTX 5090 Laptop und einem 18 Zoll großen 4K-Mini-LED-Display mit 240 Hz sowie 2.000 Dimming-Zonen. Hinzu kommen sehr gute Wartungsmöglichkeiten durch den vereinfachten Zugang zu den Komponenten und umfangreiche Individualisierungsoptionen mit AniME Vision und der vielseitigen RGB-Beleuchtung.

MediaMarkt-Aktion: 3 Switch-Spiele für 49 Euro - bei dieser Kombination spart ihr am meisten

Sun, 26 Jul 2026 10:00:21 +0200

Bei MediaMarkt bekommt ihr aktuell drei Switch-Spiele für insgesamt nur 49 Euro. Wir zeigen euch, mit welchen Titeln ihr dabei am meisten spart. Dieser Artikel wurde einsortiert unter Gaming, Schnäppchen, Nintendo Switch, Nintendo Switch Lite, Nintendo Switch 2, Nintendo Switch OLED.

Ab Donnerstag (30.7): Lidl verkauft Samsung-QLED für 299 Euro - doch dieses günstigere Modell bietet bessere Ausstattung

Sun, 26 Jul 2026 10:00:14 +0200

Lidl bringt am Donnerstag (23.07) einen günstigen Samsung-QLED-TV in die Filialen, doch ein direkter Vergleich zeigt, dass ihr für noch weniger Geld ein Modell bekommt, das bei Gaming, HDR und Ausstattung sogar die Nase vorn hat. Dieser Artikel wurde einsortiert unter Schnäppchen, Fernseher & Smart-TVs.

CLARITY Act: ein neuer Schritt zur Belohnung von Sicherh | yosreia auf Binance Square

Sun, 26 Jul 2026 06:34:14 +0200

In einer Web3-Umgebung, in der Milliarden Dollar über Protokolle und digitale Plattformen verwaltet werden, ist Cybersicherheit zu einem ...

This is one of the most interesting and comfortable gaming keyboards I’ve ever tested — but also one of the most divisive

Sun, 26 Jul 2026 06:31:00 +0200

The K63W Pro tries to do things a little differently — but are its departures a success?

New reports reveal the extent of OpenAI's loss of control during the autonomous hack on Hugging Face

Sat, 25 Jul 2026 19:50:23 +0200

In a cybersecurity test, OpenAI's most advanced models breached the boundaries of their isolated test environment, reached the open internet, and hacked the AI platform Hugging Face on their own. The attack took hours, not the weeks a human hacker would need. At least seven days passed before OpenAI realized what had happened. By then, the FBI was already involved. Earlier warning signs had apparently gone ignored.

The article New reports reveal the extent of OpenAI's loss of control during the autonomous hack on Hugging Face appeared first on The Decoder.

No, OpenAI's models didn't go 'rogue' when they broke into Hugging Face. Here's what really happened.

Sat, 25 Jul 2026 19:50:17 +0200

Experts say the models didn't "go rogue" when they escaped a controlled cybersecurity test and hacked Hugging Face. Instead, they were pursuing the goal humans had given them in ways nobody anticipated.

‘I thought, I’ve tried everything else, why not give AI a shot?’: the long-lost family reunited by ChatGPT

Sat, 25 Jul 2026 19:50:01 +0200

Avtar spent decades wondering what happened to the mother he never got to know. Thousands of miles away, Nicci was haunted by the story of a half-brother given away before she was born. How did a chatbot bring them together?

As a small boy growing up in Amritsar, India, in the 1960s, Avtar Singh used to hear whispers. Your mum isn’t really your mum, the rumours would say. Your mum lives abroad. Avtar didn’t really pay any attention to it. “I thought, the neighbours are just making up stories.” But the stories were true: the woman raising Avtar was actually his grandmother. When he was too young to remember it, his father had emigrated to Canada to work as a teacher, leaving Avtar in the care of his paternal grandparents. His grandfather, a police officer, was a fearsome authoritarian, but his grandmother brought him up with tenderness, as if he were her own son. She called him by his nickname, Titu. He felt loved.

When Avtar was around eight years old, he was told about his family in Canada: his dad, his mum and a little brother were waiting for him there, and he would soon travel to join them. Just after his ninth birthday, Avtar found himself sitting on a plane, dressed in a three‑piece suit and tie. He was travelling alone. He had never flown before. He didn’t speak a word of English. He landed in Halifax, Nova Scotia, on Christmas Eve, 1968; his family met him at the airport and took him home. “I didn’t know what to think,” Avtar, now 66, tells me in a video call from his home in Abbotsford, British Columbia. “Before I knew it, it was the first week of January, and I was put in school.”

OpenAI Says Its A.I. Models Hacked Into Hugging Face, a Digital Library

Sat, 25 Jul 2026 19:49:55 +0200

The incident, which targeted the computer systems of another company called Hugging Face, happened while OpenAI was testing the systems.

Der Remake-Boom geht an diesen 9 Gaming-Legenden komplett vorbei – die Gründe sind bitter

Sat, 25 Jul 2026 19:37:17 +0200

Die Spieleflut ist heutzutage gefühlt unendlich. Ständig gibt es neue Releases, darunter auch immer wieder Remakes und Remaster beliebter Klassiker. Einige Videospielreihen werden allerdings seit Jahren oder Jahrzehnten komplett vernachlässigt. Wir zeigen euch in dieser Bilderstrecke 9 Games, die ein Comeback mit frischem Ableger verdient haben.

OpenAI Says Its A.I. Models Hacked Into Hugging Face, a Digital Library

Sat, 25 Jul 2026 19:01:11 +0200

The incident, which targeted the computer systems of another company called Hugging Face, happened while OpenAI was testing the systems.

18 Enterprise-Architecture-Tools

Sat, 25 Jul 2026 18:59:25 +0200

Diese Enterprise Architecture Tools unterstützen Sie nicht nur bei der digitalen Transformation Ihres Unternehmens.

Foto: I Believe I Can Fly – shutterstock.com

Enterprise Architecture (EA) Tools unterstützen Unternehmen und Organisationen dabei, mit ihren IT-Strategien die Geschäftsziele optimal zu unterstützen. Sie sorgen ebenfalls dafür, dass Unternehmen ihre Roadmaps für die digitale Transformation geordnet vorantreiben können. EA Tools bieten dafür unter anderem Collaboration-, Reporting-, Testing- und Simulationsfunktionen. Mit deren Hilfe lassen sich Modelle implementieren, die Geschäfts- und IT-Prozesse gezielt verbessern.

Um die beste Lösung für Ihr Unternehmen zu finden, sollten Sie zuerst prüfen, ob sich das jeweilige Tool mit Ihrem Technologie-Stack integrieren lässt. Anschließend gilt es abzuwägen, ob die Informationen, Diagramme und Tabellen, die die Software zur Verfügung stellt, für das Unternehmen auch einen echten Nutzwert haben.

Empfehlenswerte Enterprise-Architecture-Tools

Nachfolgend finden Sie einen Überblick über die wichtigsten Enterprise-Architecture-Tools – in alphabetischer Reihenfolge. Sie stellen einen Mix aus Visualisierungs-, Collaboration- und Project-Management-Funktionen bereit und unterstützen eine Vielzahl von Enterprise Architecture Frameworks.

Ardoq

Nachdem zuerst über einfache Formulare Informationen von Usern, Entwicklern und sonstigen Stakeholdern im Unternehmen eingesammelt wurden, lässt sich mithilfe von Ardoq ein digitaler Zwilling der gesamten Organisation erstellen. Der Ansatz setzt also darauf, die Menschen, die in ihren Rollen mit den verschiedensten Systemen arbeiten, realistisch in ihrer Arbeitswelt abzubilden.

Jede Mitarbeiterin und jeder Mitarbeiter im Unternehmen kann später von den Netzwerkvisualisierungen und Datenfluss-Diagrammen profitieren, um seine eigene Rolle optimal zu unterstützen und den Arbeitsplatz immer wieder anzupassen und zu modernisieren. Das Tool lässt sich mit den wichtigsten Cloud-Plattformen integrieren. Es bietet eine API, die individuelle Anpassungen in allen wichtigen Programmiersprachen (Python, C#, Java, etc.) ermöglicht.

Wichtigste Use Cases:

“Architektonischen Stress” bei Lastspitzen simulieren, falls größere Veränderungen bevorstehen;
Verstehen, wie verändertes Nutzerverhalten neue Anforderungen generiert;
Application Portfolio Management, um besser strategisch zu planen.

Atoll Group SAMU

Das EA-Tool SAMU macht die Enterprise Architecture sichtbar, indem es tiefe Verknüpfungen zwischen On-Premises-Systemen, dem Cloud-Layer und Tools für das Business Process Management aufzeigt. Das Tool der Atoll Group bietet vielfältige Integrationsmöglichkeiten, zum Beispiel mit Monitoring-Tools (etwa Tivoli, ServiceNow), Configuration-Management-Datenbanken (zum Beispiel CA, BMC) oder Service-Organisations-Tools (BMC, HPE). Alle Informationen fließen in ein zentrales Datenmodell ein, das um den zusätzlichen Input der Stakeholder weiter angereichert wird.

Wichtigste Use Cases:

Enterprise-Architektur visualisieren;
strategische Planungsprozesse und Architektur-Reviews mit Informationen unterfüttern;
mithilfe einer visuellen Verständnisgrundlage die Kommunikation verbessern.

Avolution Abacus

Dieses Tool erfasst die Breite und den Umfang der Unternehmensarchitektur mit Hilfe eines auf Diagrammen basierenden Dashboards. Die Integration mit gängigen Tools wie SharePoint, Excel, Visio, Google Sheets, Technopedia oder ServiceNow vereinfacht die Nutzung. Abacus wurde inzwischen auch um einen Machine-Learning-Layer ergänzt, der es Anwendern ermöglicht, ein Modell zu trainieren, das ihnen beispielsweise hilft zu erkennen, wer im Unternehmen für welches System verantwortlich ist.

Wichtigste Use Cases:

die IT für das gesamte Unternehmen “öffnen”, um ein allgemeines Verständnis der Datenflüsse zu erzeugen;
umfassendes Enterprise Modeling, um eine Roadmap für künftige Entwicklungen zu erstellen;
Business-Metriken tracken, die mit der Unternehmens-Performance zusammenhängen.

BOC Group ADOIT

ADOIT soll Teams dabei unterstützen, Ressourcen zu verwalten, Bedarfe vorherzusagen und Assets zu tracken. Dazu mappt das Tool jedes System oder Softwarepaket mit einem Objekt. Die Datenflüsse zwischen den Systemen werden in Beziehungen umgewandelt, die von diesen Objekten mithilfe eines anpassbaren Metamodells erfasst werden. Geschäftsprozesse können auf ähnliche Weise über ein gut integriertes Begleitprodukt namens ADONIS modelliert werden. ADOIT ist Web-basiert und lässt sich auch mit Tools wie Atlassian Confluence integrieren, um die Datenerfassung und -entwicklung zu beschleunigen.

Wichtigste Use Cases:

ein unternehmensweites Modell erstellen, das bei sämtlichen Teammitgliedern ein Verständnis über den Stack schafft – und wie man diesen verbessern kann;
vollständiger Zugriff auf EA-Daten über eine Mobile-Anwendung;
bei Fusionen und Übernahmen den Tech-Bereich durch genaues Asset-Mapping orchestrieren.

Bizzdesign Hopex

Nach der Übernahme von Mega International zählt die Hopex-Plattform zum Portfolio von Bizzdesign. Sie soll dabei unterstützen, Unternehmensanwendungen zu modellieren und dabei ein Verständnis der von ihnen unterstützten Geschäfts-Workflows schaffen. Dabei liegt ein Schwerpunkt auf den Bereichen Data Governance und Risikomanagement. Hopex basiert auf Microsoft Azure und stützt sich auf eine Reihe offener Standards wie GraphQL und REST Queries, um Informationen aus Komponentensystemen zu sammeln. Das Reporting ist mit den Office-Tools von Microsoft sowie mit grafischen Lösungen wie Tableau und Qlik integriert.

Wichtigste Use Cases:

datengestützte Erkenntnisse herbeiführen, um Cloud- und Anwendungsbereitstellung zu steuern;
akkurate Nutzungsmodelle erstellen, um Architekturanforderungen zu verstehen;
eine Bedarfsschätzung mit Umfragen und anderen Tools vornehmen, um für die Zukunft zu planen.

Bizzdesign Horizzon

Das Tool dient dazu, Business Workflows und den zugrundeliegenden Tech-Stack zu modellieren. Dazu bietet Horizzon ein Graph-basiertes Modell, das Daten von sämtlichen Stakeholdern einsammelt und diese an eine Analytics-Engine weitergibt. Im Ergebnis entstehen Diagramme, die den aktuellen Systemzustand widerspiegeln. Wichtige Schwerpunkte dieses Tools sind Change Management und Zukunftsplanung: Horizzon ist nicht zuletzt dafür konzipiert worden, die Risiken eines Redesigns zu minimieren. Das Toolset unterstützt die wichtigsten Frameworks ArchiMate, TOGAF und BPMN. Neben Mega hat Bizzdesign im Januar 2025 auch den EA-Geschäftsbereich der Software AG – Alfabet – übernommen.

Wichtigste Use Cases:

Vorhersage zukünftiger Anforderungen durch Predictive Modeling;
Orchestrieren von Workflows auf der Basis der technischen und der Business-Architektur;
Antizipieren von Risiken sowie Security- und Governance-Problemen durch die Modellierung von Datensicherheitsanforderungen.

Capstera

Das Tool von Capstera fokussiert darauf, die Business Architecture selbst abzubilden. Value und Process Maps helfen dabei, die Rollen der verschiedenen Unternehmensbereiche zu definieren und nachzuverfolgen. Dabei können im laufenden Prozess Verknüpfungen mit den zugrundeliegenden Softwarprodukten und Tools hinzugefügt werden.

Wichtigste Use Cases:

Reports erstellen, die sich erst einmal mit der Business-Architektur selbst beschäftigen;
Beziehungen zwischen Menschen, Abteilungen und Rollen analysieren;
die langfristige strategische Planung vorantreiben.

Clausmark Bee360

Teammitglieder, die Clausmarks Flaggschiffprodukt Bee360 (früher Bee4IT) verwenden, wollen eine einfache “Single Source of Truth” über die Workflows im Unternehmen. Ziel ist es, verschiedenen betrieblichen Rollen intelligentere Entscheidungen zu ermöglichen. Das Modul Bee360 FM (Finanzmanagement) bietet etwa die Möglichkeit, Kosten nachzuvollziehen und zuzuordnen. Die Anwender können verschiedene solcher Module miteinander verknüpfen, um EAM, Finanzmanagement, Portfolio Management und Agile Planning nahtlos zu integrieren – bei maximaler Transparenz.

Wichtigste Use Cases:

C-Suite-Ebene befähigen, Projekte zu managen und Assets zuzuweisen;
präzise digitale Zwillinge entwickeln, um ein Verständnis über Datenflüsse zu schaffen und künftige Erweiterungen zu planen;
integrierte Wissensdatenbank aufbauen, um alle digitalen Workflows zu tracken.

EAS

Das Essential-Paket von EAS (Enterprise Architecture Solutions) nahm als Open-Source-Projekt seinen Anfang und hat sich inzwischen zu einer kommerziell verfügbaren Cloud-Lösung weiterentwickelt. Das Tool erstellt ein Metamodell, das die Interaktionen zwischen Systemen und Geschäftsprozessen beschreibt. Ebenfalls enthalten sind Pakete, um gängige Business Workflows wie Datenmanagement oder DSGVO-Compliance zu tracken.

Wichtigste Use Cases:

den technischen Reifegrad der eigenen Architektur evaluieren;
Sicherheit und Governance durch besseres Asset Tracking optimieren;
wachsende Systemkomplexität kontrollieren und managen.

OrbusInfinity

Orbus Software hat Anfang 2025 die Akquisition seines Konkurrenten Capsifi abgeschlossen. Der Anbieter stellt mit OrbusInfinity eine Enterprise-Transformation-Plattform auf KI-Basis zur Verfügung, die schnellere, bessere Entscheidungen, Kosteinesparungen und Risikominimierung verspricht. Architecture-Teams sollen mit Hifle von OrbusInfinity mit einer Vielzahl von Stakeholdern interagieren können, um eine “digitale Blaupause” ihres Unternehmens zu generieren, die eine einheitliche Sicht auf das aktuelle und künftige Geschäft realisieren soll. Diverse Drittanbieter-Tools lassen sich außerdem mit der Plattform integrieren, darunter etwa von Microsoft, Flexera, ManageEngine oder ServiceNow.

Wichtigste Use Cases:

Stakeholder-Management;
Enterprise-Landschaften visualisieren;
Entscheidungsfindung und Datenanalyse automatisieren.

Planview Enterprise One

Planview bietet eine ganze Reihe von Produkten, mit denen Unternehmen Teamwork, Prozesse und die Enterprise Architecture nachvollziehen können. Die Enterprise Tools sind in drei Kategorien unterteilt: strategisches Portfolio-Management, Produktportfolio-Management und Projektportfolio-Management. Im Zusammenspiel entstehen hardware- und Software-übergreifende Layer, die rollenbasierte Perspektiven für Führungskräfte und Teammitglieder eröffnen. Das Toolset integriert mit gängigen Ticket-Tracking-Systemen wie Jira, um Workflow-Analysen und Reports zu erstellen. Inzwischen hat Planview nach einer Übernahme neue Tools in sein Portfolio integriert, die früher unter den Namen Daptiv, Barometer und Projectplace bekannt waren.

Wichtigste Use Cases:

eine langfristige, strategische Vision für die Architekturentwicklung aufbauen;
Entwicklungsarbeit auf Projektebene tracken und in eine beliebige Strategie integrieren;
mit Fokus auf die Customer Experience und die Produktstruktur den Change vorantreiben.

QualiWare Enterprise Architecture

Das Enterprise Architecture Tool von QualiWare ist Teil einer größeren Sammlung von Modellierungswerkzeugen, die darauf abzielt, sämtliche Geschäftsprozesse zu erfassen. Beispielsweise ist es möglich, einen digitalen Zwillinge zu bauen, mit dem sich Customer Journeys nachvollziehen lassen. Qualiware hat diverse KI-Algorithmen integriert, um Dokumentation und Process Discovery zu optimieren.

Wichtigste Use Cases:

ein kollaboratives Ökosystem für Business Manager aufbauen, das ein Verständnis von der Enterprise Architecture vermittelt;
architektonische Designelemente erfassen, um ein Wissens-Ökosystem rund um den Stack aufzubauen;
eine breite Beteiligung in Sachen Dokumentationserstellung und -überprüfung fördern.

Quest Erwin Evolve

Das Erwin Evolve Tool von Quest hat sich von einem Datenmodellierungs-Tool zu einem System für Enterprise-Architecture- und Geschäftsprozess-Modellierung weiterentwickelt. Um die Komplexität moderner, ineinandergreifender Softwaresysteme und der von ihnen gemanagten Geschäftsprozesse zu durchdringen, können Anwender auf benutzerdefinierte Datenstrukturen zurückgreifen. Das Web-Tool erstellt Modelle, rollenbasierte Diagramme und andere Visualisierungen, die in allgemein zugängliche Dashboards einfließen. Zum Paket gehört ein KI-basiertes Modellierungs-Tool, das Whiteboard-Skizzen integrieren kann.

Wichtigste Use Cases:

einen digitalen Zwilling für die strategische Modellierung der Enterprise Data Architecture erstellen;
Customer Journeys verstehen;
Services und Systeme mit Application Portfolio Management tracken.

SAP LeanIX Enterprise Architecture Suite

Die Tool-Sammlung von LeanIX umfasst unter anderem Enterprise Architecture Management und andere Bereiche, die für Aufgaben wie SaaS– und Value-Stream-Management wichtig sind – etwa um Cloud-Deployments und darauf laufende Services zu tracken. Die Daten die dabei über die IT-Infrastruktur gesammelt werden, fließen in ein grafisches Dashboard ein. Das Tool ist eng mit wichtigen Cloud-Workflow-Tools wie Confluence, Jira, Signavio und Lucidchart integriert. Das ist für Teams von Vorteil, die diese Tools bereits nutzen, um ihre Entwicklungsstrategien zu planen und umzusetzen. Seit November 2023 ist LeanIX Teil von SAP.

Wichtigste Use Cases:

Anwendungsmodernisierung und Cloud-Migration managen;
Obsoleszenz von Software-Services evaluieren;
Kosten kontrollieren und managen.

ServiceNow

Die Tool-Sammlung von ServiceNow lässt sich auf verschiedene Architekturtypen herunterbrechen, darunter Assets, DevOps, Security und Service. Die Tools katalogisieren die unterschiedlichen Hardware- und Softwareplattformen, um Workflows und Datenflüsse im Unternehmen abzubilden und zu verstehen. Ausführliche Reportings und detaillierte Dashboards ermöglichen Analysen, auf deren Grundlage Risiken minimiert und die Ausfallsicherheit der Systeme erhöht werden können.

Wichtigste Use Cases:

Tracken von Assets, Services und Systemen, die das Unternehmen ausmachen;
Governance-Themen, Risikobegrenzung, IT-Management und Security Operations werden in einer Plattform zusammengeführt;
durch die Integration von CRM-Tools lassen sich auch kundenorientierte Services managen.

Sparx Systems

Um Teams und Projekte verschiedener Größe und Komplexität zu unterstützen, hat Sparx vier Versionen seines EA-Tools entwickelt. Allen gemeinsam ist eine UML-basierte Modellierung, mit der sich die Komponenten komplexer Systeme tracken lassen. Eine Simulations-Engine ermöglicht “War Gaming” und vermittelt ein Verständnis darüber, wie sich Fehler ausbreiten und kaskadieren können. Sparx stellt zudem eine Vielzahl von vorgefertigten Design Patterns bereit, um Teams bei der Modellierung zu unterstützen.

Wichtigste Use Cases:

Nachfrage- und Lastveränderungen zur Prognose künftiger Anforderungen simulieren;
(potenzielle) Probleme durch eine Verbindungs-Matrix im Auge behalten;
Dokumentation erstellen.

Unicom System Architect

System Architect ist eines der Angebote aus Unicoms Team Blue. Es handelt sich um ein Tool, das ein Metamodell verwendet, um automatisiert so viele Daten wie möglich über die laufenden Systeme zu sammeln – manchmal auch durch ein Reverse Engineering von Datenflüssen. Dieses systemweite Datenmodell kann über benutzerdefinierte Dashboards Teammitgliedern aller Rollen zugänglich gemacht werden. Ein weiteres erwähnenswertes Feature: Die Ressourcenzuweisung lässt sich mit Hilfe von Simulationen optimieren.

Wichtigste Use Cases:

Was-wäre-wenn-Fragen zum Architekturmodell stellen;
ein Metamodell von Daten und Systemen aufbauen;
Migrations- und Transformationspläne erstellen.

ValueBlue BlueDolphin

Dieses EA-Tool sammelt Daten auf dreierlei Art:

Es importiert Basisdaten auf der Grundlage standardgesteuerter Automatisierung (ITSM, SAM).
Es arbeitet mit den Dateiformaten von Architekten und Systemdesignern – etwa ArchiMate oder BPMN.
Es gibt Fragebögen an andere Stakeholder heraus, die auf anpassbaren Vorlagen basieren.

Die aufbereiteten Informationen werden in einer visuellen Umgebung bereitgestellt, die Auskunft über die historische Entwicklung von Systemen gibt.

Wichtigste Use Cases:

systemweite Daten von internen und externen Stakeholdern automatisiert und formularbasiert erfassen;
zukunftsorientierte Reportings erzeugen, um den Change zu überwachen und voranzutreiben;
Kooperation und Zusammenarbeit durch offenes Data Reporting fördern.

(fm)

Dieser Artikel ist im Original bei unserer Schwesterpublikation CIO.com erschienen.

Honor Magic V6 im Test: Das fast perfekte Foldable

Sat, 25 Jul 2026 18:59:23 +0200

Luke Baker

Auf einen Blick

Pro

Wunderschönes, schlankes Design
Große, helle Displays
Hervorragende Kameras
Coole Software-Funktionen

Kontra

Hoher Preis
MagicOS kann gelegentlich frustrierend sein

Fazit

Das Honor Magic V6 ist ein Falt-Smartphone, das einfach alles kann. Es ist schlank, robust, leistungsstark und sieht gut aus. Die Kameras gehören zu den besten, die Software bietet einige raffinierte Funktionen und die Akkulaufzeit ist außergewöhnlich. Besitzer eines Magic V5 werden wahrscheinlich kaum einen Grund für ein Upgrade sehen, aber für alle anderen ist es eine gute Wahl – sofern Sie es sich leisten können.

Das Honor Magic V6 wurde ursprünglich bereits im März in China vorgestellt, doch es dauerte eine Weile, bis es den Weg nach Europa fand. Nun ist es endlich in Europa erhältlich und strebt den Titel des bislang besten Falt-Smartphones an.

Leider ist die Konkurrenz für Honor stärker denn je, und sie wird noch härter werden, sobald Apples seit Langem gemunkeltes Foldable auf den Markt kommt. Bietet dieses schlanke Kraftpaket genug, um weiterhin überzeugend zu bleiben?

Es sieht auf jeden Fall vielversprechend aus, verfügt über einen der größten Akkus aller jemals erschienenen Falt-Smartphones, ist das erste mit IP69-Zertifizierung und gehört dennoch zu den dünnsten Modellen. Das ist schon mal ein guter Anfang. Ich habe es in den vergangenen Wochen auf Herz und Nieren geprüft, und hier ist mein Fazit.

Design & Verarbeitung

Aluminiumrahmen, Rückseite aus Verbundfasermaterial
219 g, NanoCrystal Shield-Glas
IP69-zertifiziert

Das Honor Magic V6 sieht dem Magic V5 sehr ähnlich, wobei der auffälligste Unterschied in der Form des Kamerarahmens liegt. Dieser ist nun kantiger und weist eine achteckige Form auf. Auch neue Farbvarianten tragen dazu bei, es von der Vorgängergeneration abzugrenzen.

Luke Baker

Die rote Version ist wahrscheinlich die auffälligste; sie verfügt über eine tiefrote, fast blutrote Rückseite mit strukturierter Oberfläche. Ich besitze die goldene Version, die ebenfalls sehr auffällig ist. Freunde haben bemerkt, dass es wie ein Smartphone aussieht, das ein saudischer Prinz oder Kim Kardashian benutzen würde.

Die Farbe schimmert leicht, wenn Licht darauf fällt; sowohl am Scharnier als auch auf der Rückseite ist ein dezentes, sich wiederholendes Dreiecksmuster zu erkennen, und es bleibt irgendwie frei von Fingerabdrücken, obwohl es ziemlich glänzend ist. Das sieht wirklich cool aus. Auch die mitgelieferte Hülle ist von höchster Qualität, mit einem cremefarbenen Kunstlederbezug und einem roségoldenen Kamerarahmen, der gleichzeitig als ausklappbarer Ständer dient.

Wenn Sie etwas suchen, das etwas weniger Aufmerksamkeit auf sich zieht, gibt es natürlich auch traditionellere Modelle in Schwarz und Weiß. Letzteres hat zudem einen versteckten Vorteil: Mit nur 8,75 Millimetern im geschlossenen Zustand ist es das dünnste Modell der Reihe, und Honor geht davon aus, dass es derzeit das dünnste Falt-Smartphone auf dem Markt ist.

Ich habe das weiße Modell nicht ausprobiert, und vielleicht ist es tatsächlich spürbar schlanker, aber meiner Meinung nach sieht die goldene Version definitiv etwas dicker aus und fühlt sich auch so wie mein 8,9 Millimeter dickes Galaxy Z Fold 7 an.

Das ist allerdings Haarspalterei, denn dieses Smartphone ist immer noch dünner als viele Flaggschiff-Smartphones im Barrenformat. Ob es nun das dünnste ist oder nicht – es ist auf jeden Fall dünn genug, um sich in der Hosentasche angenehm anzufühlen.

Luke Baker

Erwähnenswert ist auch, dass das Cover-Display nun flach ist und eine symmetrischere Form aufweist. Dadurch sieht das Smartphone im zusammengeklappten Zustand noch mehr wie ein herkömmliches Barren-Handy aus, doch die unvermeidliche, eckige Kante am Scharnier verrät es ein wenig.

So wichtig die Abmessungen eines Klapphandys auch sind, ebenso entscheidend ist die Robustheit. Und glücklicherweise ist das Honor Magic V6 robust wie ein Panzer gebaut.

Es verfügt über die Schutzklasse IP69 – die höchste aller faltbaren Smartphones. Das bedeutet, dass es praktisch staubdicht ist und sowohl das Eintauchen in Süßwasser als auch den Strahl von heißem Wasser problemlos aushält. Die Technologie der faltbaren Smartphones hat große Fortschritte gemacht.

Es ist zudem besonders robust konstruiert, mit kratzfestem „NanoCrystal Shield“-Glas auf der Vorderseite und einem „Super Steel“-Scharnier, das die Stoßfestigkeit verbessert.

SGS-Zertifizierungen untermauern diese Angaben ebenfalls, da das Smartphone für seine Fallfestigkeit mit 5 Sternen ausgezeichnet wurde. Ich habe mein Testgerät nicht allzu grob behandelt, aber es ist beruhigend zu wissen, dass es unversehrt bleiben dürfte, sollte mir einmal ein Ausrutscher unterlaufen.

Bildschirm & Lautsprecher

Außen: 6,52 Zoll, 1.080 x 2.420, OLED, 120 Hertz
Innen: 7,95 Zoll, 2.172 × 2.352, OLED, 120 Hertz
Stereolautsprecher

Bei Falt-Smartphones dreht sich alles um den Bildschirm. Beginnen wir also mit dem Star der Show: dem inneren Display. Mit einer Diagonale von knapp unter 8 Zoll gehört es zu den größten Falt-Smartphones im Buchformat auf dem Markt.

Es ist nahezu perfekt quadratisch, was sich hervorragend für die parallele Nutzung zweier Apps eignet.

Luke Baker

Dieses flexible Display verfügt über eine Bildwiederholfrequenz von 120 Hertz und erreicht eine beeindruckende Spitzenhelligkeit von 5.000 Nits. Solche Helligkeitsangaben sollten Sie zwar stets mit einer gehörigen Portion Skepsis betrachten, doch unabhängig davon handelt es sich um ein sehr helles Display, das auch im Freien gut ablesbar ist.

Der innere Bildschirm ist mit einer glänzenden Schutzfolie versehen (wenn auch mit einer Antireflexbeschichtung), was sowohl Vor- als auch Nachteile mit sich bringt. Wie ich bereits in anderen Testberichten zu Falt-Smartphones erwähnt habe, kaschieren mattierte Schutzfolien die Falz zwar besser, ziehen aber auch Fingerabdrücke an. Diese hier verschmiert nicht so leicht, doch trotz aller Bemühungen von Honor treten entlang der Falz einige unerwünschte Reflexionen auf.

Luke Baker

Apropos: Die Falz ist bewundernswert flach, und noch vor nicht allzu langer Zeit wäre sie die beste gewesen, die mir je begegnet wäre. Allerdings nutze ich das Oppo Find N6 seit seiner Markteinführung fast täglich, und leider kann dieses Modell da nicht ganz mithalten.

Es ist dennoch äußerst beeindruckend und um Längen besser als das Pixel 10 Pro Fold. Auch im Vergleich zum Galaxy Z Fold 7 fällt die Falz etwas weniger auf.

Was das Außendisplay betrifft, so ist es fast nicht von dem Bildschirm eines Flaggschiff-Handys im Barren-Format zu unterscheiden, abgesehen davon, dass es ganz leicht schmaler ist als üblich. Es verfügt über schöne, schmale Einfassungen an allen Seiten, eine flinke Bildwiederholfrequenz von 120 Hertz und eine noch höhere Spitzenhelligkeit von 6.000 Nits.

Wie bereits bei den letzten Generationen der faltbaren Honor-Modelle gibt es keine nennenswerten Nachteile bei der Nutzung des zusammengeklappten Telefons; es fühlt sich einfach wie ein normales Smartphone an. Wenn Sie dann einen größeren Bildschirm für Ihre Inhalte, Spiele oder Multitasking benötigen, klappen Sie es einfach auf.

Luke Baker

Wie üblich hat Honor einiges in Funktionen zum Augenschutz investiert, und beide Bildschirme unterstützen eine PWM-Dimmung mit 4.320 Hertz. Das werden Sie besonders zu schätzen wissen, wenn Sie empfindlich auf Flackern reagieren. Beide Bildschirme unterstützen zudem die Eingabe per Stylus, allerdings hatte ich leider keinen Honor-Stylus zur Hand, um dies auszuprobieren.

Die luxuriösen Displays werden durch ein ordentliches Lautsprecherset ergänzt. Das Stereopaar erzeugt eine schöne, breite Klangbühne, kann mehr als laut genug werden und bietet eine ordentliche Basswiedergabe. Sie können zwar nicht mit den bassbetonten Lautsprechern des Magic 8 Pro mithalten, aber bei einem so schlanken Gehäuse sind die Möglichkeiten nun einmal begrenzt.

Technische Daten & Leistung

Qualcomm Snapdragon 8 Elite Gen 5
16 GB RAM
512 GB Speicher

Das Magic V6 verfügt über den leistungsstärksten Chip von Qualcomm, den Snapdragon 8 Elite Gen 5, und das globale Modell ist mit 16 GB RAM und 512 GB Speicher ausgestattet. Bei einem so schlanken Falt-Smartphone stellt die Wärmeableitung stets eine Herausforderung dar, doch Honor hat hier eine großzügig dimensionierte Vapor-Chamber verbaut, um eine optimale Leistung zu gewährleisten.

Luke Baker

Das V6 hat meine täglichen Leistungsanforderungen problemlos erfüllt. Bei einem Falt-Smartphone habe ich oft drei Apps gleichzeitig geöffnet, wechsle zwischen ihnen hin und her und spiele häufig gleichzeitig Musik ab oder streame Videos. Selbst dann kam das Smartphone kaum ins Schwitzen.

Man muss schon ein ziemlich anspruchsvolles Spiel starten, um dieses Smartphone ein wenig ins Schwitzen zu bringen, und wie es der Zufall so will, bin ich ziemlich süchtig nach NTE: Neverness to Everness (ein Open-World-Spiel mit atemberaubender Grafik und einer riesigen Stadtkarte, mit deren Darstellung die meisten Smartphones zu kämpfen haben). Doch das Magic V6 hatte damit kaum Probleme.

Das Spiel lief bei der Grafikvoreinstellung „Extreme“ flüssig mit 60 FPS, und obwohl es sich ziemlich stark erwärmte – insbesondere im Bereich der Kamera –, schien die Leistung darunter nicht zu leiden. Die beste Erfahrung machte ich mit einem GameSir-Clamp-Controller, der die Wärme von meinen Handflächen fernhielt.

Luke Baker

Honor Magic V6 – Benchmark-Ergebnisse

Was die Benchmark-Ergebnisse angeht, wird es recht interessant. Während die meisten Ergebnisse hervorragend waren, hatte das Smartphone erhebliche Schwierigkeiten, den 3DMark Wildlife Extreme Stress Test abzuschließen. Normalerweise führe ich diesen Test bei aufgeklapptem Smartphone durch, doch es überhitzte sich und brach den Benchmark jedes Mal ab, wenn ich es versuchte.

Zugegebenermaßen war es in letzter Zeit recht warm, doch so etwas ist mir bisher noch nie passiert. Bei der Durchführung des Tests auf dem Cover-Display konnte es den Test mit einem ordentlichen Ergebnis abschließen, auf dem klappbaren Bildschirm war dies jedoch nicht möglich. Im alltäglichen Gebrauch hatte ich jedoch nie derartige Probleme.

Kameras

50-MP-Hauptkamera mit f/1,6
64 MP, f/2,5, 3-fach-Tele
50 MP, f/2,2 Ultraweitwinkel
20 MP, f/2,2 Selfie-Kamera

Das Honor Magic V6 verfügt über dieselbe Kamera-Hardware wie die Vorgängergeneration, was bedeutet, dass es keine nennenswerten Neuerungen gibt.

Allerdings verfügte das V5 bereits über eine der beeindruckendsten Kameraausstattungen unter allen faltbaren Smartphones, und die Konkurrenz hat sich in dieser Hinsicht nicht sonderlich ins Zeug gelegt – daher gehört es nach wie vor zu den Besten.

Luke Baker

Auf der Rückseite befindet sich eine 50-MP-Hauptkamera mit einem Sensor von ansehnlicher Größe (1/1,56 Zoll) und einem lichtstarken f/1,6-Objektiv. Hinzu kommen eine 50-MP-Ultraweitwinkelkamera mit einem extrem weiten Sichtfeld (entspricht 13 mm) sowie ein ausgezeichnetes 64-MP-Teleobjektiv. Außerdem gibt es zwei 20-MP-Selfie-Kameras, von denen jeweils eine durch das jeweilige Display ragt.

Dies ist eine äußerst vielseitige Objektivausstattung, mit der Sie alles aufnehmen können – von weitläufigen Landschaften bis zu intimen Porträts. Wie üblich hat mir die Verwendung des Teleobjektivs am meisten Spaß gemacht, und dies könnte die beste Tele-Kamera sein, die jemals in einem faltbaren Smartphone verbaut wurde.

Es verfügt über einen recht großen 1/2-Zoll-Sensor und kann aus sehr kurzer Entfernung fokussieren. Ihr Motiv muss sich lediglich etwa 20 Zentimeter vom Objektiv entfernt befinden, und in Kombination mit der Brennweite von 70 mm (äquivalent) entsteht so eine schöne perspektivische Kompression und ein natürliches Bokeh.

Natürlich können Sie mit einem digitalen Ausschnitt noch weiter zoomen, und die Kamera-App ermöglicht Ihnen auf Wunsch eine bis zu 100-fache Vergrößerung. Bei einer Vergrößerung von mehr als 10-fach können Sie generative KI nutzen, um die Bilder zu bereinigen, doch auch ohne diese Funktion erhalten Sie bereits bei etwa 20-facher Vergrößerung brauchbare Bilder.

Ich habe bereits erwähnt, wie weitwinklig das Ultraweitwinkelobjektiv ist, und das gefällt mir besonders gut daran; ansonsten ist es jedoch im Vergleich zu den anderen Objektiven definitiv ein Qualitätsverlust.

Nachts ist es zudem am wenigsten überzeugend, da Bewegungsunschärfe dort nur schwer zu bewältigen ist. Bei den richtigen Lichtverhältnissen ist es jedoch zu wirklich beeindruckenden Aufnahmen fähig.

Luke Baker

Die Hauptkamera ist wie immer die zuverlässigste des Trios. Dank des größeren Sensors schneidet sie bei schlechten Lichtverhältnissen am besten ab und liefert tagsüber etwas schärfere Bilder als die anderen Kameras.

Die Selfie-Kameras sind nichts Besonderes. Sie erfüllen ihren Zweck und eignen sich für Zoom-Anrufe, doch wenn man auf der Rückseite so beeindruckende Kameras hat, lohnt es sich wirklich, das Smartphone umzudrehen und den Bildschirm auf der Rückseite zu nutzen, um wirklich beeindruckende Fotos zu machen.

Die Bildverarbeitung von Honor kann etwas unbeständig sein, aber ich habe den Eindruck, dass sie immer konsistenter wird, und wenn sie funktioniert, lassen sich wirklich atemberaubende Bilder erzielen.

Mein größter Kritikpunkt ist die Bewegungsunschärfe im Porträtmodus. Ich bin mir nicht sicher, woran es liegt, aber ich erhalte viele unscharfe Aufnahmen, wenn die künstliche Hintergrundunschärfe aktiviert ist – selbst bei guten Lichtverhältnissen.

Ansonsten bin ich mit den Bildern, die ich mit dem Magic V6 aufgenommen habe, sehr zufrieden. Die Harcourt-Porträtmodi sind so beeindruckend wie eh und je, und mit den übrigen Filtern lässt sich der Look Ihrer Fotos ziemlich drastisch verändern. Besonders gut gefällt mir der Filter „Nostalgic Negative“, der einen schönen, kontrastreichen Cross-Entwicklungs-Look mit blauen Schatten erzeugt.

Was die Videoaufnahmen angeht, ist das Angebot etwas weniger umfangreich. Das soll nicht heißen, dass es schlecht ist, aber nachdem ich viel Zeit mit dem Oppo Find N6 verbracht habe, habe ich mich an ein ordentliches Log-Profil, 4K-120-Aufnahmen und Dolby Vision gewöhnt. Nichts davon ist hier vorhanden. Es gibt zwar ein Log-Profil, dieses funktioniert jedoch nur mit dem Hauptsensor und erzeugt ungewöhnlich körnige Schatten.

Wenn Sie jedoch keine ganz so professionellen Ansprüche haben, werden Sie mit der Videoleistung wahrscheinlich sehr zufrieden sein. Sie können mit jeder Kamera bis zu 4K bei 60 FPS aufnehmen, mit Ausnahme der Selfie-Kamera, die maximal 4K bei 30 FPS erreicht. Die Bildstabilisierung ist gut, und auch die Mikrofone sind ordentlich.

Akkulaufzeit & Aufladen

6.660-mAh-Akku
80-Watt-Laden über Kabel
66 Watt kabelloses Laden

Das Honor Magic V6 verfügt über den größten Akku aller faltbaren Smartphones, die ich bisher getestet habe. Irgendwie ist es Honor gelungen, einen 6660-mAh-Akku in dieses hauchdünne Gehäuse zu integrieren. Samsun wird hoffentlich davon lernen.

Diese Kapazität verblasst zwar im Vergleich zur chinesischen 1-TB-Version dieses Smartphones, die über einen erstaunlichen 7.150-mAh-Akku verfügt, doch wie wir in letzter Zeit oft gesehen haben, bedeuten die EU-Vorschriften, dass wir im Westen keinen ganz so massiven Akku erhalten können.

Luke Baker

Das spielt jedoch keine allzu große Rolle, denn dieser Akku ist mehr als gut genug. Obwohl ich den großen internen Bildschirm häufig nutzte und unzählige Fotos machte, reichte die Akkulaufzeit dieses Smartphones während des Großteils meiner Tests für eineinhalb Tage. Natürlich verkürzt intensives Gaming die Laufzeit etwas, aber Sie werden das Gerät selten, wenn überhaupt, vor dem Schlafengehen aufladen müssen.

Auch das Aufladen erfolgt schnell, vorausgesetzt, Sie verfügen über ein ausreichend leistungsstarkes Netzteil (im Lieferumfang ist lediglich ein USB-C-Kabel enthalten), um die 80-Watt-Geschwindigkeit nutzen zu können. Ich konnte das Gerät in nur einer halben Stunde von leer auf fast 70 Prozent aufladen; mehr kann man sich kaum wünschen.

Wenn Sie kabelloses Laden bevorzugen, ist dies ohne nennenswerte Einbußen bei der Geschwindigkeit möglich. Das Honor Magic V6 lässt sich mit einem offiziellen kabellosen Ladepad von Honor mit bis zu 66 Watt aufladen.

Software & Apps

MagicOS 10, basierend auf Android 16
Zahlreiche KI-Funktionen
Kompatibilität mit dem Apple-Ökosystem

Auf dem Magic V6 läuft MagicOS 10, Honors eigene Variante von Android 16. Es handelt sich im Wesentlichen um dieselbe Software, die wir bereits von den letzten Honor-Flaggschiffmodellen kennen. Wenn Sie also bereits eines dieser Modelle ausprobiert haben, werden Sie kaum Überraschungen erleben.

Luke Baker

Die Software von Honor kann die Meinungen spalten. Sie weicht ziemlich stark vom typischen Android-Erlebnis ab; stattdessen erinnert sie zunehmend an iOS. Ob das nun gut ist oder nicht, hängt ganz von Ihren Vorlieben ab.

Allerdings lässt sich die Benutzeroberfläche extrem gut anpassen – wenn Ihnen also das Design oder das Layout einer Funktion nicht gefällt, können Sie es höchstwahrscheinlich ändern.

Insgesamt gefällt sie mir recht gut. Sie wirkt schnell und reaktionsfreudig, sieht standardmäßig ansprechend aus und bietet zahlreiche Werkzeuge zur weiteren Anpassung. Wie bereits erwähnt, gibt es zahlreiche Anlehnungen an iOS, darunter einige „Liquid Glass“-ähnliche Elemente, einen „Dynamic Island“-Klon, geteilte Benachrichtigungen/Schnelleinstellungen sowie die Möglichkeit, die App-Übersicht zu deaktivieren.

Das sind zwar nicht die originellsten Entscheidungen, aber sie funktionieren gut, und die meisten sind vollkommen optional.

Honor bietet Ihnen eine Vielzahl von KI-Funktionen, darunter die üblichen Tools für Transkription, Übersetzung und Zusammenfassung sowie einige sehr fortschrittliche Funktionen zur Fotobearbeitung.

Luke Baker

Auch das Multitasking ist hervorragend. Sie können Apps im Split-View nebeneinander anzeigen und dann eine dritte hinzufügen, die nur am Rand des Bildschirms hervorblitzt und bei Bedarf sofort einsatzbereit ist. Oder, wenn Sie es vorziehen, können Sie schwebende Fenster nutzen und so noch mehr Inhalte gleichzeitig auf dem Bildschirm anzeigen.

Am spannendsten finde ich jedoch die Art und Weise, wie sich das Magic V6 in Apple-Produkte integrieren lässt. Insbesondere, wie gut es mit meinem Macbook zusammenarbeitet. Wenn Sie die Honor Workstation-App aus dem Mac App Store installieren, können Sie Dateien austauschen, zwischen Geräten kopieren und einfügen, Ihr Smartphone fernsteuern und das V6 sogar als drahtlosen zweiten Bildschirm nutzen.

Luke Baker

Doch damit ist der Spaß noch lange nicht vorbei. Das Honor Magic V6 kann auch nativ Dateien in Ihrem iCloud-Konto durchsuchen und verwalten, und mit Honor Connect können Sie Dateien auch per AirDrop zu und von iPhones übertragen. Das ist großartig, wenn Sie ständig zwischen verschiedenen Ökosystemen hin- und herwechseln (wie ich es oft tue).

Insgesamt ist es also ein solides Software-Erlebnis, das jedoch nicht ganz ohne Nachteile ist. Meine größte Kritik an Honor-Smartphones ist seit einigen Jahren unberücksichtigt geblieben. Das Akkumanagement ist extrem aggressiv und beendet standardmäßig Hintergrund-Apps mit rücksichtsloser Härte.

Das bedeutet, dass Sie häufig unter stark verzögerten Benachrichtigungen leiden, bis Sie einige Einstellungen anpassen und sicherstellen, dass diese Apps geöffnet bleiben.

Luke Baker

Das lässt sich zwar leicht beheben, und ich kann die Logik dahinter nachvollziehen – schließlich bieten Honor-Smartphones stets eine hervorragende Akkulaufzeit –, doch es ist äußerst ärgerlich, und ich würde mich sehr freuen, wenn dieses Problem behoben würde.

Honor verspricht sieben Jahre lang Software-Updates und Sicherheitspatches für seine Flaggschiff-Geräte und liegt damit auf einer Stufe mit Samsung und Apple. Viel besser geht es kaum, auch wenn Sie möglicherweise eine Weile auf das auf Android 17 basierende MagicOS 11 warten müssen.

Preis & Verfügbarkeit

Das Honor Magic V6 kann ab sofort in Deutschland und den meisten anderen Ländern der Welt bestellt werden, wobei die USA wie üblich ausgeschlossen sind. Hierzulande liegt der Preis bei stolzen 2.299 Euro, wobei es bis zum 31. Juli noch einen Rabatt von 600 Euro gibt (Endpreis: 1.699,90 Euro).

Als besonderes Einführungsangebot legt Honor auch eine Reihe kostenloser Extras wie ein Tablet, einen Stift und ein Set Earbuds bei. Das macht eine Beurteilung des Preises ziemlich schwierig. Auf dem Papier ist das Magic V6 deutlich teurer als das V5, das im vergangenen Jahr für 1.999 Euro auf den Markt kam. Und das schmerzt, insbesondere wenn man bedenkt, dass es seinem Vorgänger so ähnlich ist. Mit dem Rabatt ist es jedoch günstiger.

Preislich bewegt es sich trotzdem noch in einem ähnlichen Rahmen wie viele andere Falt-Smartphones, die wir getestet haben. Darunter das Motorola Razr Fold, das Samsung Galaxy Z Fold 7 und das Google Pixel 10 Pro Fold.

Sollten Sie das Honor Magic V6 kaufen?

Das Magic V6 ist zweifellos eines der attraktivsten faltbaren Smartphones, die derzeit auf dem Markt erhältlich sind. Die Hardware ist hervorragend, die Bildschirme sind beeindruckend, es ist leistungsstark und die Kameras sind erstklassig. Wenn Sie ein faltbares Smartphone mit großem Bildschirm suchen, aber bei den Kameras keine allzu großen Abstriche machen möchten, ist dies eine hervorragende Wahl.

Allerdings könnten versierte Käufer sich für das Vorjahresmodell entscheiden und für deutlich weniger Geld ein sehr ähnliches Gesamterlebnis erhalten. Es ist nach wie vor extrem leistungsstark und verfügt über dieselben Kameras. Es wird jedoch nicht ewig vorrätig sein.

Man sollte auch bedenken, dass das Galaxy Z Fold 8 und das Z Fold 8 Ultra voraussichtlich im Juli 2026 erscheinen werden, während Apples lang erwartetes faltbares iPhone wahrscheinlich im September vorgestellt wird. Ich persönlich würde mir daher erst einmal ansehen, was diese Modelle zu bieten haben, bevor ich den Sprung wage.

Wenn Sie nicht warten können, ist das Honor Magic V6 eine hervorragende Wahl und wird dies wahrscheinlich auch bleiben. Ich kann mir nicht vorstellen, dass Samsung die Akkukapazität übertreffen wird, und ich bezweifle sehr, dass es in puncto Kameraleistung übertroffen wird. Abgesehen von ein paar kleinen Software-Mängeln ist es ein brillantes Smartphone.

Technische Daten

MagicOS 10, basierend auf Android 16
Außen: 6,52 Zoll, 1.080 x 2.420, OLED, 120 Hz
Innen: 7,95 Zoll, 2172 × 2352, OLED, 120 Hz
Fingerabdrucksensor im Ein-/Aus-Schalter
Qualcomm Snapdragon 8 Elite Gen 5
16 GB RAM
512 GB Speicher
Kamera:
50 MP, f/1,6 Hauptkamera
64 MP, f/2,5, 3-fach-Teleobjektiv
50 MP, f/2,2 Ultraweitwinkel
Doppelte 20-MP-Selfie-Kamera mit f/2,2
Videoaufnahmen mit bis zu 4K bei 60 fps (Rückkamera)
Stereolautsprecher
Dual-SIM
WLAN 802.11 a/b/g/n/ac/6e/7
Bluetooth 6.0
6660-mAh-Akku
80-W-Laden über Kabel
66 W kabelloses Laden
156,7 × 74,5 × 8,8 mm (zusammengeklappt)
IP69-zertifiziert
219 g
Farben: Gold, Rot, Weiß, Schwarz

(PC-Welt)

Smaller, smarter, safer: How to build agentic AI on the right foundation

Sat, 25 Jul 2026 18:55:52 +0200

When it comes to building an effective AI stack, context is king and power isn’t everything it’s cracked up to be.

“Smaller, smarter, safer — this is a bet our company has taken in how we deploy AI internally,” said Ricky Thakrar, head of sales and account management at Zoho, provider of a suite of popular cloud-based software solutions for sales, marketing, and finance.

“I’m on the business side, and so decisions made by our CIO and IT folks affect me directly, and my teams’ workflows and processes,” he added.

Speaking to a room of tech leaders at the CIO 100 Leadership Live New York event last week, Thakrar explained that every company wants the speed of AI-generated work wedded to the quality of human work, even though these two are diametrically opposed. No amount of model upgrades or spend will close that gap, so the only way forward is to architect your way out. Thakrar encapsulated this idea in a simple formula:

Smaller: Stop deploying maximum firepower on every task. Many tasks don’t need it.
Smarter: The system around the model decides more than the model does.
Safer: Verify at the point a mistake gets locked in, not just downstream of it.

He noted that organizations that win with AI won’t be those deploying the biggest, most powerful models or the most sophisticated architecture, but the ones that figure out that the model is the easy part and the right architecture is harder. That means understanding the hardest element, and the biggest differentiator, is building a human system that learns and compounds alongside agentic systems.

To get it right, organizations need to prioritize the context layer. The size of frontier models like the GPT series, Claude, and Gemini mostly exist to compensate for missing context, Thakrar explained. Without enough context, models need to be able to reason harder and infer more about what a user actually means because it doesn’t know the user’s account, process, or history. A rich context layer makes it possible for enterprises to run workloads on much smaller, lower-power models.

“The intelligence moves from the model into the architecture around it,” he said.

A steep learning curve

One of Zoho’s earliest AI agents was a churn management agent to help the account management team detect churn in customer subscriptions. So when a subscription became inactive, the agent would collect context from notes, meeting recordings, and Zoho’s data enrichment tool, then create a summary of reasons the account might have churned, and schedule a call.

“What happened was I got this churn agent a couple months later, already embedded in our CRM, and within a week my team no longer trusted that agent,” Thakrar said. “The reason is we forgot to collect one very key point.”

In Zoho’s CRM, when a customer buys a bundle of products, that bundle is represented as a single line item. That means the status of any products the customer may have previously purchased individually changes to inactive as they’re moved to the bundle. That’s not churn, but it was interpreted it that way. Zoho fixed it in the second version of the agent.

Then a new problem arose. Many potential customers first purchase Zoho products as pilots or sandboxes. As those customers move from pilot to live instance, they close down the pilot versions. And again, the CRM would record that as subscriptions going inactive.

“The trust deteriorates again because everyone got excited for version 2,” Thakrar said.

Sometimes, a certain product might not be the best fit for a customer and Thakrar’s team will suggest the customer move to another product. That’s deliberate churn, not a churn risk.

“You may have a similar story like this where the agent sounds so good, it’s going to do something quick and add value, but it’s missing context from the account managers, and there are so many more pieces we’re still building out,” Thakrar said. “It’s been almost a year and the problem I have is my team still doesn’t trust it. They’ll see [a message from the agent] and go out and do all the research anyway to make sure it gave the correct answer.”

The team is more on top of potential churn, though, but the promised productivity gains have yet to materialize because the agent has to earn back lost trust due to a lack of context.

“My goal for this year is having an AI-assisted customer journey from sales to account management where the handoff is clean, the context flows, and every piece of information we gather about a customer is weighed, identified, and coached so the sales team can close more deals,” he said.

Zoho’s early experience with agents has led to the idea that constrained, context-rich, deterministic architectures consistently outperform expensive models bolted onto fragmented systems. It all comes down to three pillars: routing, harness, and specialization.

Routing

Routing is about sending workloads to the proper model for the job, which entails providing enough context to a given task that a small, cheap model can handle it without the need for spare reasoning capacity to fill gaps.

Frontier models are expensive and companies can burn through a year’s budget worth of tokens in months. But most tasks can be handled by much smaller, more constrained models at a fraction of the cost.

“You don’t always have to pay the frontier guys for every task,” he said. “We’ve observed with some clients that we could save them 95% with a 3 billion parameter model.”

Harness

An AI agent harness is the software infrastructure scaffolding around an LLM that differentiates an agent from a chatbot. It’s what enables an agent to act on tasks rather than simply respond to prompts. A model reasons through a problem and decides what to do about it. The harness connects the model to the tools, systems, memory, guardrails, and execution environments required to perform the actions determined by the model. The term is frequently used more or less interchangeably with orchestration layer.

“It’s the process around the model, which matters way more than the model itself,” Thakrar said.

In benchmark tests, a superior harness on a less powerful model produces better results than an inferior harness on a much bigger model.

For the best results, Thakrar said, it’s essential to understand the deterministic and non-deterministic elements of a given workload, and build that into the architecture. Machines can read, organize, and validate, and they excel at deterministic tasks. Humans, on the other hand, are exceptional at non-deterministic tasks like judging, synthesizing, and deciding.

Those non-deterministic tasks in a process are the ideal point for AI agents to incorporate a human in the loop, what Thakrar calls human harness. He pointed to a stakeholder mapping agent Zoho built for sales as an example, which takes the context of an initial meeting and third-party enriched data like a LinkedIn profile, weighs probabilities, and makes an educated guess about the stakeholder map.

“The initial goal was just to eliminate that task completely from the human workflow,” he said. “The stakeholder map is done, it’s in the folder, and you can look at it.”

But the agent would struggle to capture nuance. The meanings of titles in organizations always vary, and the politics and dynamics of any given meeting can be difficult for an AI agent to discern. Rather than keep feeding the agent data to try to make it intelligent enough to make those determinations, it was simpler and more efficient for the agent to create a proposed stakeholder map and hand it over to a human who could make changes and explain why those changes were necessary.

Ultimately, Thakrar said the agent still saved human team members time because the stakeholder map was usually pretty close, and the corrections also helped the model grow smarter by adding richer context.

Specialization

Specialization is transitioning a process from testing on a frontier model to production on a much narrower, smaller model. Once you’ve proven that an agent can do a job well, you want to stop paying master-craftsman rates to keep doing that one job well.

Specialization is all about capturing your subject matter experts’ best judgement and pattern recognition to build an open-weight, open source, trained, and fine-tuned model that can be deployed in your own data center.

“The true enterprise bet is to keep that orchestration layer, which is your IP and knowledge, in house,” Thakrar said. “You don’t want to host that on someone else’s model. The goal of everyone in enterprise should be to run, train, and host their own models.”

Why I changed how I pitch AI: It’s no longer about saving money, but managing tokens and adoption

Sat, 25 Jul 2026 18:55:49 +0200

I have worked alongside enterprise technology for more than 30 years and watched AI evolve from a lab experiment into the modern boardroom’s core focus. However, the last few years of implementing AI alongside our customers have delivered our most profound reality checks.

The initial hype has faded, leaving CIOs to drive real enterprise value. Based on my experience implementing Google, OpenAI and Anthropic technologies, here are the fundamental, technology-agnostic lessons every leader must anchor their strategy around.

AI as a leadership multiplier

The most common tactical error we see is treating AI as an isolated technology project. What I have observed among our customers is that true success does not come from organizations that define a standalone “AI strategy,” but rather from those leaders that integrate AI into their business strategy.

When our customers isolate AI and define an AI strategy, it inevitably treats it like a “technological toy” to experiment with. This approach yields fragmented, orphaned initiatives that fail to scale because they are fundamentally disconnected from their core corporate objectives. What I learned is that AI is not the ultimate destination; it is a powerful catalyst. We have replaced “What can AI do for our customers?” with a more strategic question, “How does AI accelerate their existing business goals?”

Think of AI like electricity. No modern corporation designs a standalone “electricity strategy.” Instead, all companies route it invisibly across the entire organization to illuminate offices, power production lines and drive communication. AI must be woven into the enterprise fabric in the exact same way, acting as an underlying utility that supercharges your existing operational model.

Integrating AI into the broader business strategy also dictates how we measure success. It forces a shift away from short-term tech vanity metrics and anchors the technology into a long-term roadmap.

When AI remains trapped within the IT department of our customers, we notice that it is relegated to a mere “software experiment.” To become a true competitive advantage, we observed that AI requires intense cross-functional orchestration. This perspective does not diminish the merit of the technical team; their expertise is fundamental for establishing the architecture, data governance and tools your enterprise requires. However, while IT builds the foundational infrastructure, it lacks the organizational authority to decide what should be built on top of it. Only the CEO or the owner of the company can step in to ensure AI leaves the “toy project” phase and integrates into the DNA of the organization.

The requirement for top-down, executive ownership stems from three critical realities observed in the field:

Silo-smashing and data collaboration: True enterprise AI is data-hungry and that data lives across disparate business lines, finance, operations, marketing and customer service. Only the CEO possesses the cross-functional authority to demand that data silos be dismantled.
Cultural transformation and fear mitigation: AI triggers widespread anxiety over job displacement across all industries and hierarchies. When relegated to an “IT project,” resistance spikes as teams view it as a threat to their livelihoods. When I saw the CEO lead this cultural shift directly is when I noticed the best results.
C-Suite education and strategic alignment: The mandate for AI capability cannot just be delegated downward; the transformation must begin at the very top. I have conducted more than 70 presentations for the Board of Directors and C-Level teams. These people need to be actively educated not on technical code, but on specific business use cases, return on investment (ROI) frameworks and how AI resolves core organizational bottlenecks.

PwC’s data found that only 12% of enterprises have achieved both cost and revenue benefits from AI. Those elite 12% succeeded precisely because their CEOs embedded AI extensively across strategic decision-making and cross-functional workflows. AI is simply too disruptive and too critical to be left exclusively in the hands of technical experts. If AI is not on the CEO’s weekly agenda, it is fundamentally missing from the company’s true strategy.

AI as a new operational framework

Traditional IT systems have operated on strict algorithmic certainty: if you input a specific set of data, the system executes an immutable line of code and guarantees the same, predictable output every single time.

AI completely breaks this paradigm. Because modern AI is built on probabilistic models, it does not execute static formulas; instead, it predicts the most likely correct response based on mathematical probabilities. This means that AI solutions carry an inherent, small percentage of uncertainty and variability. A prompt entered today might yield a slightly different, though contextually valid, output tomorrow.

Executive leadership and organizational cultures must be actively educated to accept and navigate this fundamental shift. Traditional quality assurance frameworks for software are designed for a 100% success rate. Applying this rigid standard to AI will paralyze your initiatives, keeping 80% of your projects trapped eternally in the pilot phase. This happened to us in a food and beverage company in Latin America a couple of years ago. After this experience, we started to include conditions in our contracts that tolerate statistical margins of error and still define the project as a success.

In terms of cost calculation, we had to teach CIOs and business managers to forget the monthly subscription model for AI and learn to manage the primary unit of exchange in modern AI: the token.

To understand AI costs, executives must understand how large language models process data. AI models do not read full words; instead, they break text, images or code down into “pieces” called tokens. As a baseline, every 100 words process as approximately 130 to 140 tokens. Because the major AI providers use the token as their currency, your business is billed dynamically based on the exact volume of tokens consumed by every query submitted (input) and every response generated (output).

Many leaders believe AI costs are fixed due to flat-rate enterprise tiers ($25–$30/user). This is a temporary illusion. These venture-capital-subsidized rates mask true operational costs and come with dynamic usage limits. Modeling long-term ROI on them guarantees a severe budget shock when true consumption pricing takes over.

The solution is not to halt AI adoption; doing so means losing your competitive edge. Instead, the cost per token must cease to be treated as a technical footnote relegated to the IT department. It must be elevated to a core business variable.

Risks in the AI adoption model

Since the beginning of the AI boom, I have seen all our customers making a critical tactical error that could cost them heavily in the medium term: they are focusing only on operational efficiency (reducing costs with AI).

I have observed that an alarmingly high percentage of companies remain trapped in pilot phases focused exclusively on short-term cost reduction. Bain & Company’s global Automation and AI Pathfinder Survey found that the largest share of companies measuring their AI initiatives (exactly 40%) realized cost reductions of 10% or less, heavily missing their internal targets. Our customers are putting too many resources and effort into marginal financial gains and in doing so, they are jeopardizing their most valuable assets: service quality, resilience and customer trust.

Utilizing AI solely to slash headcount or cut operational corners is a dangerous trap that introduces severe field liabilities. A financial service organization in Latin America announced that they saved $1 million in customer support by replacing humans with AI chatbots. However, the mid-term reality revealed a different story: a damaged brand reputation due to AI errors and an influx of frustrated clients fleeing because the automated system cannot handle special cases.

Putting a company on an extreme AI diet might make it look leaner on next quarter’s financial statement, but over-indexing on cost-cutting will ultimately leave the business too weak to compete when market dynamics shift. We are now inviting our customers to change the question from “How much money will AI save us?” to “How will we leverage AI to exponentially increase the long-term value of our enterprise?”

Deploying enterprise AI is a marathon, not a sprint, and the terrain changes with every mile. The organizations that thrive in this next era will be those that transition from fascination to discipline, treating AI not as a magic bullet for immediate savings, but as a core capability that demands rigorous governance, architectural foresight and cultural maturity. Navigating this shift requires moving past the theoretical hype and anchoring decisions in raw, field-tested reality.

As we continue to deploy these technologies across industries, the blueprint for success is being rewritten in real time. Let’s keep this conversation going as we map out the future of business intelligence together.

This article is published as part of the Foundry Expert Contributor Network.
Want to join?

5 endpoint blind spots your EDR/XDR was never built to see

Sat, 25 Jul 2026 18:55:47 +0200

In August 2025, 126 malicious packages landed in the npm registry. Even after the community caught the initial wave, 80 of these hidden backdoors remained actively listed.

That was enough. Over 86,000 downloads. Malicious code in PhantomRaven, packages running in the production systems of Fortune 500 companies worldwide. And throughout the entire window, not a single EDR/XDR alert.

This happened because the attack surface has expanded to a layer EDR/XDR was never designed to see: VS Code extensions, local MCP servers, and rogue AI coding assistants that inherit your engineers’ valid credentials to steal data at machine speed.

To eliminate this structural vulnerability, Palo Alto Networks acquired Koi, an AI-native developer security product engineered for proactive, precision enforcement. Below we compiled a 2026 CISO checklist you can use to audit your environment and see how Koi automates each defense from day one.

#1. Gain real-time visibility into shadow AI & extensions

Your existing asset management tracks binaries and installers, but it cannot see local VS Code extensions, MCP servers, or ad-hoc Python scripts running on developer endpoints. This visibility gap was recently exposed by the MaliciousCorgi campaign, where two marketplace extensions with 1.5 million combined installs silently harvested every file a developer opened. Neither triggered any detection because they were not binaries, not executables, not anything your inventory was built to flag. To counter this, Koi closes the gap by analyzing what extensions actually do after installation, exposing hidden data-harvesting channels running inside your active workspace.

#2. Distinguish between human and autonomous agent behavior

When a rogue AI agent exfiltrates your proprietary source code, it uses a developer’s valid credentials during normal working hours, making the session look entirely legitimate to standard XDR baselines. Moving beyond static permission lists, Koi deploys behavioral profiling within the workspace runtime. By actively intercepting unauthenticated background tasks and blocking unauthorized file-system reads, it stops automated data exfiltration in real time.

#3. Establish guardrails for automated package updates on endpoints

Developers prioritize speed, often allowing software packages to auto-update on their endpoints the moment a new version appears. Attackers weaponize this supply chain vulnerability, as seen in the May 2026 Team PCP attack where 3,800 GitHub repositories were compromised in just 36 minutes via poisoned auto-updates. Securing agentic endpoints against these rapid breaches requires behavior-based inspection within the active workspace context. Koi operates at this layer by providing safe deployment buffers that automate version cooldowns, blocking bleeding-edge updates until they are vetted. By continuously auditing process creation within the IDE runtime, Koi instantly drops unauthorized remote connections before malicious payloads can exfiltrate credentials from the endpoint.

#4. Enforce principle of least privilege for AI agents

AI coding assistants inherit the privileges of whoever deployed them. In practice, that means read access to production databases, write access to core repositories, and access to every secret in environment files and configuration directories. To restrict this excessive access, Koi applies dynamic sandboxing directly to AI agent processes at the kernel level. It enforces a strict zero-trust boundary that segregates sensitive workspace vectors, preventing agents from pulling data outside their approved scope without interrupting developer workflows.

#5. Maintain continuous endpoint posture management

Signature-based scanning only stops known threats. Sophisticated repository attacks often arrive as functional, high-rated software that carries no known bad signature. Koi’s research into the DarkSpectre campaign found eight browser extensions, all carrying “featured” badges from Google and Microsoft, installed by over 8 million users, silently harvesting every conversation from ChatGPT, Claude, and Gemini in the background. Koi addresses this by operating upstream: scanning marketplace listings every hour, using LLM-driven code analysis to compare what software promises against what its code does, sandboxing it, and scoring the risk before it ever reaches the endpoint.

Summary

Securing the modern enterprise is no longer about patching individual gaps. As AI agents redefine the workforce, Agentic Endpoint Security (AES) is now a strategic imperative for every CISO. By establishing a mandatory control plane for the AI-native workspace, AES ensures that your organization can scale engineering velocity without ever compromising enterprise integrity.

Ready to secure the future of your software stack? See how Koi Agentic Endpoint Security delivers complete visibility, risk scoring, and real-time prevention across every endpoint in your enterprise.

OpenAI's Rogue Agent Went Unnoticed For a Week

Sat, 25 Jul 2026 18:52:27 +0200

An anonymous reader quotes a report from Reuters: The OpenAI agent that broke into tech firm Hugging Face went on a dayslong hacking spree that OpenAI didn't notice until well after the threat was contained and the FBI was alerted, according to people familiar with the investigation. The agent -- a program capable of making decisions and executing complex tasks with little or no human oversight -- attempted to break out of its isolated testing environment at OpenAI around July 9, according to two of the people. The intrusion at Hugging Face, which operates as a repository for AI tools and models, began two days later on July 11 and lasted until July 13, said Thomas Wolf, Hugging Face's co-founder. It took several more days for OpenAI to realize its agent was behind the hack, and the two companies only communicated about it for the first time on or around July 20, according to Wolf and three of the people familiar with the investigation. OpenAI's public disclosure, on July 21, thatone of its agents had slipped out of control and carried out the break-in at Hugging Facedrew global attention. But many details of the hack, including how long the agent went rogue and OpenAI's belated knowledge of it, are being reported here for the first time. Hugging Face is preparing a public timeline of the hack, Wolf said, adding that he could not speak to what happened at OpenAI. In a statement, OpenAI said the hack was unprecedented and "marks an important moment for AI safety." It added that it was reviewing the incident with outside advisers and would eventually publish a technical report. "Does that mean that they left it unattended and didn't realize what it was doing? Or maybe they did and didn't know how to contain it? Both are equally dangerous and alarming," asked Marley Smith, the principal intelligence specialist at the nonprofit World Ethical Data Foundation. "The models lie, they cheat, they hack," said Jeffrey Ladish, whose organization, Palisade Research, studies the capabilities and motivations of AI agents. Ladish said the hack should spark broader questions over how much all the leading AI companies are willing to invest in onerous security measures while locked in a race with one another to deploy the best and fastest models. "There has to be government oversight," Ladish said, "because it won't happen otherwise."

Read more of this story at Slashdot.

Ryzen 7 9800HX3D: AMD plant wohl erschwingliche Gaming-Laptop-CPU

Sat, 25 Jul 2026 18:51:55 +0200

AMD bereitet angeblich einen neuen X3D-Laptop-Prozessor für anspruchsvolle Gamer vor. Die kommende CPU soll voraussichtlich acht Kerne besitzen und auf bis zu 5,1 GHz takten. Die offizielle Vorstellung der mobilen CPU wird für Anfang 2027 erwartet. (Weiter lesen)

The Valve Steam Machine should be the perfect 'couch gaming' PC—but after testing it out, I'm not convinced it's worth the price

Sat, 25 Jul 2026 13:03:54 +0200

Valve's long-awaited Steam Machine is finally here – but was it really worth the wait? I've gone hands-on to find out.

Build for the future with the Android XR Developer Catalyst Program — Apply now!

Sat, 25 Jul 2026 10:15:51 +0200

Posted by Android XR Team

The Android XR ecosystem is expanding, and we’re committed to supporting developers who will build its next great experiences. Today, we’re opening applications for the Android XR Developer Catalyst Program, a dedicated initiative to accelerate the development of Android XR apps ready to launch within the next year.

This program is designed to provide the resources, hardware, and grants to help you build and scale innovative experiences across wired XR glasses, like XREAL’s Project Aura, and intelligent eyewear (audio and display glasses). We are especially interested in seeing innovative experiences across media, gaming, productivity, and health, but we welcome any unique use case that helps users expand what's possible.

Why join the catalyst program?

We want to help developers navigate common barriers to entry for XR development by providing:

Development Kits: Get early access to hardware development kits for wired XR glasses (XREAL’s Project Aura) and / or intelligent eyewear (audio and display glasses).
Technical support: Gain access to specialized technical resources and support forums specifically designed to help you prepare your app for Google Play.
Grant Opportunities: Submit a request and you may be eligible to receive a non-recoupable grant to accelerate your development.

Ready to start building?

Applications are open to developers looking to publish apps for the Android XR ecosystem in the next 6-12 months. You can build with Kotlin and the Jetpack XR SDK, or with Unity, Unreal Engine or Godot. If you need a spark of inspiration, you can check out existing XR Experiments and Samples to see how you can use the SDK for everything from spatial music to navigation.

Once you have your concept ready, be sure to submit your application by June 30th by 11:59PM PDT. We can’t wait to see what you build.

Start Your Application

Explore this announcement and all Google I/O 2026 updates on io.google.

Valve Will Finally Let You Build Your Own Steam Machine With SteamOS For Desktop

Sat, 25 Jul 2026 10:12:56 +0200

With the price of the new Steam Machine starting at $1,049, you might want to consider making your own Steam Machine instead. An anonymous reader quotes a report from The Verge: Valve says that "starting with the SteamOS 3.8 release, you can put together your own Steam Machine using whatever PC parts you want." SteamOS 3.8.10 launched last week with a slew of updates, including "improved compatibility with recent Intel and AMD platforms." Alongside that improved compatibility, Valve is giving gamers the green light to install SteamOS on their own desktops. In an interview with The Verge, Valve's Pierre-Loup Griffais said Valve has been "rolling out improvements to [SteamOS] so it's more compatible with desktop hardware," including eventual support for Nvidia graphics. Griffais says Valve has "a growing team" working on Nvidia driver support for SteamOS, adding, "We're collaborating with Nvidia very closely." While he mentioned that Nvidia support might not come this year, Griffais emphasized that "it's certainly something that we're working on in the background." It's technically been possible to run SteamOS on your own hardware for a while now, but compatibility has been mostly limited to AMD systems. So far installing it has also required using a Steam Deck recovery image, a process that, speaking from experience, is much less straightforward than the installation process for most other Linux distributions. Trying to run SteamOS on Intel or Nvidia hardware has not been easy so far. According to Griffais, Valve is working to change that, which could mean that down the line, you'll be able to run SteamOS on just about any gaming PC hardware you want, including Nvidia. For the more immediate future, Griffais says SteamOS in its current state should offer a "good experience" on console-like PC setups: "If you have something that is similar to the use case of a Steam Machine, where you have a PC that's gonna be plugged into a TV, and has a single hard drive that you're not going to try and dual boot [] you can put SteamOS on there, and you'll have an experience that is very similar to a Steam Deck docked or a Steam Machine, with some caveats, of course," like a lack of HDMI-CEC support. But "the core bits of the experience are there. The SteamOS graphics driver, the shader precompilation [...] you can get at all of that with the SteamOS." Griffais says SteamOS does not yet offer an easy way to dual-boot alongside Windows or another operating system, but envisions "a time where it's a better experience to install on your desktop and have it coexist with a different operating system."

Read more of this story at Slashdot.

Valve Releases Proton 11 With Huge Linux Gaming Improvements

Sat, 25 Jul 2026 10:12:46 +0200

BrianFagioli writes: Valve has released Proton 11.0-1, a major update to its Windows compatibility layer for Linux that makes more games playable while fixing a long list of bugs affecting existing titles. The release restores compatibility for many EA games after a recent EA App update, moves classics like Resident Evil (1996), Resident Evil 2 (1998), Dino Crisis, and SHOGUN: Total War from Proton Experimental into the stable release, and adds support for games including Gothic 1 Classic, X-Plane 12, Breath of Fire IV, and Deadly Premonition. Valve also fixed crashes in HELLDIVERS 2, restored No Man's Sky VR support, improved Steam Overlay compatibility with EA games, addressed KDE and GNOME desktop issues, and rebased Proton on Wine 11.0 with updated graphics components. The full list of changes can be found here.

Read more of this story at Slashdot.

So krass war die erste Höllenmaschine - HMX 6

Sat, 25 Jul 2026 10:10:51 +0200

Author: PC-WELT - Bewertung: 6x - Views:216

10.000€ wert und für 2006 absolut crazy Hardware: Das war die Höllenmaschine 1.

Das HMX 6 Gaming-PC-Gewinnspiel ist gestartet und du könntest ihn gewinnen!

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Mit etwas Glück gewinnst du die HMX 6. 🍀
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Dell Alienware AW3226DM im Test: 32-Zoll-Gaming-Monitor mit 240 Hertz

Sat, 25 Jul 2026 10:09:47 +0200

Viel Bild, viel Tempo, günstiger Preis: Der Dell Alienware AW3226DM setzt auf eine Kombination, die bei Gamern derzeit besonders gefragt ist. COMPUTER BILD hat geprüft, wie gut sich der 32-Zöller im Alltag und im Labor schlägt.

Firefox Nightly: Giving You More Control – These Weeks in Firefox: Issue 204

Sat, 25 Jul 2026 08:37:31 +0200

Highlights

Maxx Crawford added a pref to hide the New Tab logo so users can opt out of branding without altering page layout or resorting to CSS overrides.
Harshit enabled video overlay detection in Nightly 153, allowing you to use the context menu to control videos on more pages! We plan on letting this ride out in Firefox 153.
- You can try it out on this Instagram reel in Nightly

A note to WebExtension authors – as part of a planned deprecation announced last month, executeScript and insertCSS are now restricted from moz-extension pages starting in Firefox 152 – Bug 2015559
Nicolas Chevobbe [:nchevobbe] added support and debugging for modern attr()(which is enabled on Nightly) (#2014751)

Friends of the Firefox team

Resolved bugs (excluding employees)

Script to find new contributors from bug list

Volunteers that fixed more than one bug

Sam Johnson
Sebastian Zartner [:sebo]

New contributors (🌟 = first patch)

Immaculate Atim: Switch to using an array instead of an object string for browser.backup.enabled_on.profiles
liz: Screenshots overlay visible on both splitview browsers
🌟 Rahman Mahmutović [:r_m]: Can’t change content in box model in inspector for box-sizing:border-box elements
Takeru Mitsumori: Fix typo in ID name about-translations-swap-langauges-icon in about-translations.html
🌟 Freya Arbjerg [:freyacodes]: Blackboxed columns are ignored
tom.passarelli: tab-preview-panel emits unpaired popupshown/popuphidden events, breaking sidebar autohide

Project Updates

Add-ons / Web Extensions

Addon Manager & about:addons

As part of the work for the Project Nova about:addons page restyling, the about:addons sidebar has been migrated to the moz-page-nav and moz-page-nav-button reusable components, improving accessibility and visual consistency with the Firefox Desktop about:settings page – Bug 1881767

WebExtensions Framework

Implemented WebExtensions negative permissions infrastructure, providing the foundations for enterprise policy “blocked host permissions” features – Bug 1745823
Restricted host permission changes for MV3 extensions force-installed via enterprise policy (matching similar behaviors provided by Chrome enterprise policy behaviors) – Bug 1904054
- Thanks to Mike Kaply for the implementation of this enterprise policy enforcement feature.

WebExtension APIs

Fixed handling of as an API permission in Manifest V3, ensuring the permission is correctly initialized on extension install – Bug 1758306

DevTools

Rahman Mahmutović [:r_m] made it possible to edit width/height in the box model section of the Layout panel (#1717176)
Sebastian Zartner [:sebo] improved toggling tools driving in-page highlighters (e.g. the Measuring) (#1262773)
Sebastian Zartner [:sebo] added a setting to control visibility of HTML comments in the markup view (#1455294)
Freya Arbjerg [:freyacodes] fixed an issue in script blackboxing (#2036767)
Alexandre Poirot [:ochameau] replaced custom preference to log RDP messages with MOZ_LOG (#1622857)
Alexandre Poirot [:ochameau] fixed retrieval of garbage collected script text content (#1758454)

WebDriver

Sameem updated the “Take Element Screenshot” command from WebDriver Classic to crop screenshots of elements which exceed the viewport. This aligns with the specification and avoids errors when attempting to capture huge elements.
Alexandra Borovova updated the events for new top-level browsing contexts: we will not send anymore “browsingContext.domContentLoaded” and “browsingContext.load” events for them, instead the “browsingContext.contextCreated” event will be sent when a tab is ready to be used. This is required to align with the expected per-spec behavior.
Henrik Skupin landed a patch allowing geckodriver to gracefully shut down Firefox when geckodriver itself is terminated.
Hiroyuki Ikezoe disabled Firefox’s “scroll axis lock” feature so WebDriver actions for wheel input devices can scroll in arbitrary directions when using pan gestures.

Lint, Docs and Workflow

Added a rule to prevent new uses of Preferences.sys.mjs.
The browser environment globals within ESLint have now been updated. These include Sanitizer, VideoFrame and a few other new ones.
Temporal, and some other definitions have been added to TypeScript.

New Tab Page

Much has happened in the last 2 weeks! Here’s a full bug list, and here are some highlights.
Dre fixed the List widget that was creating a new list too eagerly on the New Tab Page (2033592) — prevents accidental list creation and improves the Lists UI reliability.
Maxx Crawford fixed Weather widget small card layout issues with opt-in location options and an error message displayed, resolving card overflow and removing the spurious opt-in error so users see a compact Weather card and correct location prompts on New Tab.
Reem Hamoui added key dates state to the Sports widget, enabling the Sports card to surface event deadlines/key-date highlights on New Tab so sports users see timely date info.
Scott Downe added a manage widgets option to the New Tab nova widgets context menu, giving users a direct context-menu entry to open the widget management flow from any widget with Nova enabled.
Scott Downe added a reusable Newtab widget base component to centralize lifecycle, focus/keyboard handling, DOM templates, and telemetry hooks, reducing duplication and making widget behavior more consistent; see Newtab widget base component.
Dre converted per-widget expansion handling to a shared widget expansion handler to unify expand/collapse state management and prevent widgets from incorrectly retaining or losing expanded state; see Convert widget expansion handling to shared widget expansion.
Nina Pypchenko [:nina-py] updated the Sports widget to populate the “follow teams” state from the /teams endpoint, so follow/unfollow toggles now reflect server-side subscriptions and reduce incorrect follow states.
Scott Downe moved widget menu items within New Tab widgets to standardize menu ordering and action grouping, so users find Add/Remove/Configure entries in expected positions across platforms.
Dre fixed a World Clock city search bug for the word clocks widget, restoring expected search filtering/matching so city lookups return correct results.
Scott Downe fixed an issue where the New Tab small weather widget size change didn’t always apply by correcting the widget size update path (JS/CSS layout interactions), improving consistent rendering for small-tile weather across responsive breakpoints and platforms; see Newtab small weather widget size change doesn’t always work.
Nina Pypchenko [:nina-py] added a group stage section to match highlights in the sports widget on New Tab so users now see stage-aware grouping and stage labels on match highlight cards, making tournament context (group vs knockout) visible while browsing highlights.
Dre fixed the small world clock widget not expanding to large while editing clocks so users can enter edit mode and expand the widget as expected; the change wires the edit-mode resize handler to update widget size/class during edits.
Maxx Crawford added WCW OMC message strings so World Cup widget messaging flows on New Tab now display the correct copy (localized where available) instead of falling back to missing-text behavior.
Reem Hamoui added a “View all” button and a list view for the results tab at medium widget size so Sports widget users on medium New Tab tiles can expand results and scroll full lists without resizing the widget.
Maxx Crawford added WCW “Watch Live” stream strings to the Sports widget strings bundle so the widget can surface a localized “Watch Live” CTA for applicable events.
Dre restored VoiceOver reachability for Edit/Remove in World Clock on macOS so macOS VoiceOver users can now focus and activate clock Edit/Remove controls thanks to accessibility role/label and focus-order fixes.
Maxx Crawford removed the persistent browser logo when all new-tab features (Top Sites, widgets, content feed) are disabled by adding a conditional render guard in the New Tab component, preventing an orphaned logo (2041033).
Mike Conley added New Tab jest tests to the node tests Tier 1 CI job Run newtab jest tests as part of node tests Tier 1 job to catch regressions earlier in CI
Irene Ni shipped multiple visual fixes for the Sports widget Sports widget – various visual fixes (spacing, truncation, icon alignment, clipping) to improve readability and layout on constrained viewports.

Picture-in-Picture

kpatenio adjusted our YouTube site specific wrapper so that the URL bar toggle appears more reliably, especially when selecting videos from the YouTube search page.
Thanks to Sylvestre for patching some bugs to prevent some spurious console errors!
Niklas fixed captions on autopip videos failing to sync with the origin videos.

Performance Tools (aka Firefox Profiler)

Firefox Profiler now has a CLI! We also added a profiler-analysis skill to the Firefox codebase. Once you capture a performance profile, you can ask Claude or an AI to analyze it by providing a link or local path. You can use it to analyze a performance regression or debug an issue if you have a profile at hand.
- https://www.npmjs.com/package/@firefox-devtools/profiler-cli
- You can install it with npm install -g @firefox-devtools/profiler-cli@latest

Search and Urlbar

Nova UI refresh

Drew and Daisuke continued working on reorganizing styles and updating the urlbar for Nova.
2019154, 2019152, 2041501, 2040532

Suggest

Drew landed several Suggest improvements: realtime suggestions colors, sports suggestions received World Cup tweaks, and online Suggest via OHTTP was enabled for eligible users in Firefox 153.
2040561, 2039753, 2035614, 2038843

Adaptive autofill

James fixed soft-block counting to track autofill dismisses, rather than consecutive backspaces on the same autofill, and added telemetry to measure URLs reintegration after blocking.
2040819, 2037177

Quick actions

Dharma created a new Firefox Labs quick action, fixed the Update action button, and re-enabled ScotchBonnet in some tests that were not updated yet.
Caleb added Calculator support for certain unicode operators.
2023169, 1928635, 1923383, 2033861

Multi Context Address Bar

Moritz continued refactoring the urlbar code: converted some of the js modules to not be system modules, fixed dynamic results templates, incorrect reuse of result rows, and keyboard shortcuts on the unified search button panel.
2039297, 2036095, 2039844, 2037933, 2030050

Other

Marco, Drew and Daisuke fixed several intermittent test failures.
2038510, 2023908, 2011584, 1938142, 1971091

Search

Mark removed old WebExtension-based search engines from the source tree, removed loading of search add-ons from resource://search-extensions/.
Caleb fixed multiple documentation issues and added a test covering searches from a private window.
1904613, 2035878, 2037942, 2033545, 2005724

Places

Marco removed some unnecessary database transactions, fixed the bookmarks panel folder dropdown on Windows, and resolved several intermittent test failures.
Thanks to Sam Johnson who fixed the bookmark edit panel showing “mobile” instead of “Mobile Bookmarks”.
2039534, 1505800, 2008829, 2029541, 2035084

The Rust Programming Language Blog: The many journeys of learning Rust

Sat, 25 Jul 2026 08:37:24 +0200

This is another post in our series covering what we learned through the Vision Doc process. We previously described the overall approach and what we learned about doing user research, we explored what people love about Rust, dug into what it takes to ship safety-crticial Rust, and described some of the major challenges that people face when using Rust.

In this post we walk through what folks have found on their journey to learn the Rust programming language with ups and downs covered.

As a disclaimer, LLMs (Large Language Models) come up in this post because our interviewees brought them up. We're scoping discussion to their use as a learning tool, covering research and example generation, not broader questions about AI (Artificial Intelligence) in software development.

Many paths to needing Rust

The interviews surfaced several different paths into Rust: curiosity, embedded work, job-market pressure, organizational adoption, and reassignment after a team or company chose Rust. That last path matters because many learners are not evaluating Rust from a blank slate; they are trying to become productive after Rust has already arrived in their work.

"Funny enough, I've advocated for more niche languages than Rust in the past. Rust has pretty much stopped being as much of a niche language as it was, but it's not Java." -- Fractional CTO

Rust learning resources

Likely as expected, the folks that we talked to reach for a range of resources to learn Rust. Some reach for official documentation, such as The Rust Programming Language Book and find that sufficient to build on what the compiler was already showing them.

"I started with the official Rust documentation because there are a lot of great examples of how features like the borrow checker work." -- Software engineer at an Automotive supplier

Others needed more passes and more formats, sometimes reaching for resources the community maintains, such as Rustlings, The Little Book of Rust Macros, and Learn Rust With Entirely Too Many Linked Lists.

"The first time I went through the chapter in [The Rust Programming Language] on borrow checking, I was like, what is this? I read it again, then I watched a YouTube video of someone explaining the chapter." -- Rust freelance consultant

"Rust book, Rustlings, Zero to Production in Rust, Jon Gjengset tutorials. A bunch of books. It's not a one-pass reading. Can't say how many times I've gone through it." -- Software engineer working on video streaming and storage

These resources have brought up an entire generation of Rust programmers. But, to some, there is a perception that these resources have trouble keeping pace with the language.

"We'd like to use [The Rust Programming Language/'the book'], but we've found that it's out of date, unfortunately. We've looked at the GitHub repo and found it's got a lot of unresolved issues and unmerged PRs" -- Principal Software Engineering work on Rust adoption in a regulated industry

Whether or not this is factually true, Rust's growth has nonetheless put more scrutiny on these materials. Companies evaluating adoption and engineers getting reassigned to Rust teams are looking at them with fresh eyes and finding the gaps that affect their own evaluation.

Beginner stumblings and unlearning habits

It's pretty typical for Rust to be the 2nd, 3rd or Nth programming language that someone picks up. They'd end up writing their most familiar language in Rust, whether C++ patterns, Java patterns, or whatever they knew, for months or even years. Eventually they got comfortable enough to start writing idiomatic Rust.

"There's a bit of a drop in productivity compared to C if you're already familiar with it just because you're learning new rules, new syntax." -- Principal Firmware Engineer (mobile robotics)

"In the beginning it was more poking around the code and adding and removing some ampersands and asterisks to try to make sense of mut and not mut and whatever." -- Senior engineer with 20 years of Java experience in cloud and IoT

We also spoke with someone who found that not having much of a programming background seemed to benefit people picking up Rust. Not having worn-in grooves from other languages may play a role here, and it's worth investigating further.

"I had someone who had never programmed much before start working on the internals of [our Rust project]. She was just fine with getting into Rust. It's more of the senior people that struggle as they need to unlearn practices which may work in other languages, but it's not the 'Rust' way." -- Researcher, Automotive OEM R&D Lab

Learning to work with the borrow checker

We heard a lot about learning to work with the borrow checker instead of against it. People get there through different paths, but a few patterns came up repeatedly.

The compiler as teacher

Rust's diagnostics did the teaching on their own, especially around lifetimes.

"If you mess up the lifetimes in a piece of code that you've written by hand, I usually find that Rust's diagnostics are very helpful" -- Researcher working on static analysis of Rust programs

"Whatever's missing, the compiler usually fills in: it tells me 'you need to declare the lifetime of this reference', so I know and can figure it out. That all generally works pretty well." -- Senior Software Engineer

Learning by doing

Others felt like they only really internalized the borrow checker after writing a lot of Rust. It took projects, coding challenges, prototyping and so on until at some point it clicked.

"I actually did not understand the borrow checker until I spent a lot of time writing Rust" -- Founder of a startup built on Rust

"Besides the prototyping work, I also did coding-challenge-type stuff to get familiar with Rust for Advent of Code. [..] It eventually clicked to the point where I wasn't fighting with Rust, it was working for me. I had that experience other people describe: when I managed to get my program to fit with Rust, it worked. I didn't spend time debugging." -- Principal Software Engineer, large SaaS provider

Letting go of "clone guilt"

Some learners arrive with the assumption that good Rust means zero clones, zero copies, lifetimes threaded through everything. They set the bar at optimal before they've learned how to write idiomatic Rust, and it makes the borrow checker feel harder than it needs to be at the outset.

"On one of my first projects, I was like, 'I don't ever want to copy or clone anything,' so I carefully wove through all the lifetimes and got myself into a bit of a bind. Then I saw someone else just cloning the struct I was working with, and it was super cheap. Sometimes you can just clone and it's going to be okay." -- Researcher at a university

The experienced Rust developers we spoke with consistently said the same thing: clone freely while you're learning, then optimize when you understand the problem. Rust's reputation for performance and correctness feeds this. Newcomers assume anything less than optimal is wrong before they've written a first working program, and clone guilt is how that shows up.

We think it could be an interesting area of future study to check into the patterns Rust programmers employ at different levels of experience and under which circumstances. One member of the Rust Vision doc team that's very experienced with Rust noted that there's kind of an "expected shape" they understand as passing the compiler. This knowledge influences how they approach writing code which wouldn't take that shape and they naturally find themselves understanding when to use so-called workarounds, such as passing around indices into arrays or Vecs.

Multi-paradigm, but not the OOP some are used to

The Rust programming language is multi-paradigm, and how that lands depends on what you're coming from. We heard some that came from a functional background were delighted with digging into learning how much Rust inherits from that lineage. Some others noted that they and others on their teams struggled to unlearn the object-oriented style they'd come to use heavily in other languages like C++ and Java.

"Developers coming from C++ tend to think object-oriented. I think that's a difference between C++ and Rust." -- Architect at Automotive OEM

"I had exactly that thing, where I would apply all my years of Java and JS thinking, where I could just create some object, not care about it, return it, have it sloshing around between various functions. Found myself reaching for these patterns and then being told 'no, you cannot do that'." -- Principal Engineer at a SaaS company

Developers coming from functional programming had less to unlearn: strong typing, pattern matching, and an expression-oriented style were already familiar.

"My background has been more functional programming, strong typing. That originated for me as a Lisper: once a Lisper, always a Lisper." -- Principal Software Engineer working on Rust tooling for safety-regulated industries

"The languages I primarily used before Rust were things like OCaml. Way back, I came from C and C++, the classic languages, and then I spent quite a long time doing primarily pure functional stuff. These days I've ended up back in what I like to think of as a pragmatic center ground [with Rust]." -- Fractional CTO

Teaching Rust in academia

We spoke with a university professor that's been teaching Rust generally. In the academic environment, they were able to use proxies for some things such as "traits are like interfaces in Java" because the students had already gone through a set of courses in their first and second years that taught them Java. They introduced concepts slowly throughout the course, choosing to deal with some more complex topics like generics later. The outcome generally was that students had no problem picking up Rust in this setting.

"I couldn't see any big difference on the embedded side. We also teach an embedded class, and we did an experiment. Half of the students' feedback was worse on the Rust class, mostly because they needed to build the project themselves. The C students just got one from [an LLM], absolutely no problem." -- University Professor, on teaching Rust

The C cohort leaned on LLMs for the project in ways the Rust cohort couldn't. We don't yet have a clear answer for why.

What did come through clearly was the Rust cohort's experience with the community. Some students needed to figure out which drivers to use for the embedded project and how to use them. Their professor encouraged them to open issues and ask questions directly on GitHub, and the maintainers responded. Students who had never contributed to open source before were getting answers from the people who wrote the code.

Learning using LLMs

Some experienced folks shared that they saw LLMs as a tool that can help someone come up to speed quickly, either as a research tool or for generating example Rust code to understand concepts.

"I'm optimistic that there's a way to work [LLMs] in that will cut down that learning curve. One of the big things these tools bring is reducing the learning curve in general; these are very good tools to help you navigate a space that you don't know yet." -- Maintainer of large open source Rust crate

"I try [LLMs] out once a month, usually for generating an example or something like this. Just like with Stack Overflow: when you read an example, you should read it carefully and try to understand it. Not copy and paste it, but type it in your own words in code and then check it, because that's where the teeny tiny little mistakes are." -- Founder of startup built on Rust

For some learners, an LLM is just another way to find answers, no different than a search engine.

"So for the most part, picking up Rust - how do I learn? I'll [use web search for] things, I'll ask [an LLM], I'll just poke around and read the code." -- Senior Software Engineer working in a regulated space

One founder went further and claimed that LLMs change who can become a Rust developer. One consulting company founder described hiring high school graduates with no systems programming background and training them as Rust developers, with LLMs filling in the learning gaps that would previously have required years of experience.

"At the beginning, I was worried, but now that we have [LLMs] supporting development, the difficulty of the language doesn't matter. I'm seeing a huge opportunity behind strong runtime languages like Rust. [..] In [Developing Country] we hire 20-25 high school graduates, train them to be Rust programmers, then they enhance our workforce worldwide." -- Founder of a consulting company

We heard this from one organization. This is a claim that the combination of Rust's compiler and LLM tooling can dramatically shorten the path from beginner to working developer. Whether it generalizes depends on questions we can't answer from a single interview: how long these developers stay, what kind of code they can maintain independently, and whether this training/learning model works outside this company's particular structure. If it holds up, the pool of people who can become Rust developers is much larger than the usual hiring profile suggests.

Organizational considerations for Rust learners

We spoke with a number of folks on teams that are using Rust in larger organizations. Teams wanted to know that everyone would end up at roughly the same level of competence, which led a good number to invest in training courses to get there. Some leaders found that staff was able to ramp well enough by reading The Rust Programming Language, going through Rustlings, and then picking up lower risk and priority tickets to work on. Having a sense of community was also important within companies; it helps people know they are not alone when they are asked to work on Rust after, say, a reorganization happens.

"[..] the idea with the class as opposed to 'just read the Rust book on your own' was that this gives everyone kind of the same baseline going in." -- Principal Firmware Engineer (mobile robotics)

"So typically we're going to have people work through Rustlings, work through The Rust Programming Language. We have them then start to pick up lower risk tickets to work on." -- Principal Engineer at a large SaaS provider

"We've got an internal Slack channel for Rust learning where people can drop questions and others will come in and answer them. That helps build up understanding and community." -- Software Engineer at a large corporation

Some organizations found that while the person they'd hire would need to learn Rust, it was still preferable to the alternative of hiring someone for a critical piece of software written in another language.

"They needed to grow and maintain this C++ codebase. They had a C++ wizard, and they tried for about two years to find someone with the same level of expertise. They ended up hiring people that didn't know Rust and ramping them up, creating FFI bindings from the C++ side so they could work in Rust. And you can feel it: the borrow checker is teaching these people the right way to handle their systems." -- Principal Engineer at an Automotive OEM

The community and helping each other aspect seems to grow bonds as organizations mature.

"Our team is [all about] mentorship. I've mentored people coming up to speed on Rust, and people help each other hugely." -- Principal Software Engineer at a large SaaS company

Silent attrition

We identified some cases where people have approached Rust and bounced off of it, for one reason or another. In the below case, someone with a background in a language with fewer guardrails found themselves frustrated enough with Rust to walk away.

"All of that means that that embedded ecosystem is very frustrating to somebody who comes from C and is like, why can't I just get a pointer to this peripheral and then write into the registers. What are you doing to me? [..] My friend never got over that. He looked at it and said, I'm not going to deal with this and walked away." -– A second University Professor

There may be language features that for a particular domain are not seen as comfortable or usable yet, such as async Rust usage in a safety domain. We'd like to map which language features feel off-limits in which domains; async in safety-critical work probably isn't the only case.

"We're not fully sure how async [Rust] will work out in the long run in our domain. [..] People don't feel comfortable yet since C++14 doesn't provide such concepts. [..] It's the chicken-and-egg problem again: we probably need to gain some experience to see whether we can actually benefit from these new concepts in the automotive and safety domains." -- Team Lead at Automotive Supplier (ASIL D target)

We heard in at least one case, that while the language was challenging and there was a near bounce, the tooling helped keep them coming back and trying.

"Well, I think my early impressions of Rust - one is I find C++ so intimidating, and I think a big part of why I was able to succeed at [..] learning Rust is the tooling. I mean, all this makes sense [..] but it's like, for me, getting started with Rust, the language was challenging, but the tooling was incredibly easy." -- Founder of another startup built on Rust

While it might be considered more of a community concern, if there are interactions online and in spaces that point to learners having so-called "skill issues" this feeds into the narrative that Rust must be hard to learn. We may be unintentionally turning away Rust Project contributors and maintainers due to the vibes being put out when new learners show up in certain spaces.

"People are very helpful, but generally the attitude is: if your program is very complicated, it's mostly a skill issue. There's not that much empathy when people get stuck learning, and a lot of people are just pushed away by it. There's probably a huge number of people who silently stop wanting to write Rust, because at some point it gets complicated and the feedback they get is 'you just need to be a better programmer, obviously'." -- Software Engineer at a SaaS Provider

Feedback on near-bounces from survey

We found a few interesting perspectives collected in the Rust Vision doc survey which we administered with examples of bouncing and coming back:

"I started before 1.0, got stuck very soon when trying to translate patterns from C++ to Rust (due to borrow checking). I tried again after 1.0 and it stuck. [..]" -- Survey Respondent A

Survey Respondent A went on to share in a more detailed response about a perceived weakness in Rust learning materials related to lifetimes and the borrow checker are explained. There was an observation that it's fairly easy to run into more complex situations with lifetimes and the borrow checker. They felt that the current state of this sort of material and tutorials is fairly superficial and can leave learners stuck when they run into those more complex situations.

One respondent that bounced once and came back shared challenges around usage of async. In concert with Rust's memory-safety and the borrow checker, they found some of the nitty-gritty details of async were difficult to learn. While we're aware of the Rust Project's continuous efforts to improve Rust's async story, this is another data point of a user that faced challenges.

Another survey respondent shared how they had multiple times bounced in trying to learn Rust. They returned after a year or so and found Rustlings to be highly motivating. We note that having multiple pathways for folks to learn Rust opens up more possibilities for those that nearly bounced, just like this person.

Need more focused work on silent attritrion

The thing that stood out most to us was the lack of real, first-hand knowledge of having bounced when learning Rust. While this is an obvious effect of soliciting answers to our survey and opportunities to interview through Rust channels and our networks, this cohort is good future candidate where interviews could start.

Conclusions

Across these conversations, the experience of learning Rust depended heavily on context. Why someone was learning and what support they had mattered as much as the borrow checker. The same kinds of examples kept coming up: a training course that got a team to a shared baseline, a maintainer answering a student's first GitHub issue, and a colleague whose code showed that cloning was okay.

That context is largely something the community has a hand in. With that in mind, here is what we take away from what we heard, and what we still don't know.

What seems worth trying

Learning materials aimed at unlearning. Syntax barely came up when people described their struggles. People struggled with unlearning habits from previous languages, whether OOP structuring from C++ and Java or the instinct to grab a raw pointer to a peripheral. Most of our learning materials teach Rust from first principles, and that works. What we didn't come across is much written for, say, the engineer with ten years of Java who lands on a Rust team after a reorg: material that names the patterns they'll reach for that won't transfer, and shows what to do instead. The professor we spoke with did a version of this in the classroom, leaning on "traits are like interfaces in Java" and saving generics for later in the course, and the students did fine. Something similar could work outside the classroom too.

Put the "clone freely while you're learning" advice somewhere official. Every experienced developer we spoke with gave the same advice, but learners seem to mostly pick it up by accident, like the researcher who happened to see someone else cloning the struct they had been carefully threading lifetimes through. Saying it early in official materials would take some of the steepness out of the curve. The broader version belongs there too: idiomatic Rust doesn't have to mean optimal Rust, especially on a first project.

Diagnostics are already a primary learning resource: several people told us the compiler taught them lifetimes before any documentation did. Diagnostics reach learners right at the moment they're stuck. When writing new ones, it seems worth keeping the confused newcomer in mind alongside the expert, because for a lot of people this is where the learning happens.

Is "the book" actually out of date? Whether or not The Rust Programming Language or other materials are actually behind, a team evaluating Rust looked at its repository, saw unresolved issues and unmerged PRs, and moved on. As more companies evaluate adoption, more people will look at these materials with the same fresh eyes. Visible issue triage and some communication about what's current and what's planned would address the perception, separately from whatever content work may or may not be needed.

How stuck learners get treated is shaping who stays. We heard about students getting answers on GitHub from the maintainers who wrote the code, and we heard about learners being told their struggles were a skill issue. The first group came away with a lasting good impression of Rust. Some of the second group walked away entirely, and because they leave quietly, it's easy to underestimate how many of them there are. The welcoming side of the community came up unprompted as a reason people stayed, so we know it makes a difference when we get this right.

Every organization we spoke with described essentially the same ramp-up for bringing a team to Rust. Teams that brought groups of developers to Rust described roughly the same approach: get everyone to a shared baseline with a training course or with The Rust Programming Language and Rustlings, start people on lower-risk tickets, and give them somewhere internal to ask questions. Several organizations also found that hiring developers without Rust experience and ramping them up worked out better than continuing to search for rare expertise in another language. None of this is complicated, and teams weighing adoption don't need to invent a training program from scratch.

What we still don't know

The biggest gap is the people we didn't reach. Nearly everyone we spoke with stuck with Rust long enough to be reachable through Rust channels, so the stories of bouncing off came to us second-hand: a friend who walked away from embedded Rust, colleagues who quietly stopped after the responses they got. As we wrote in our first post, finding people who decided against Rust takes targeted outreach. If the proposed User Research team comes together, talking with learners who bounced would make a good early project, and learning is probably the area where that research would teach us the most.

We also don't know what to make of LLMs as a learning tool yet. They came up as a search engine, as an example generator, and in one organization's case as something that makes training high school graduates into working Rust developers possible. We saw a classroom where the C cohort leaned on LLMs in ways the Rust cohort couldn't, and we don't have an explanation for it. All of this comes from a handful of conversations, so we treat it as a set of leads to follow up on. Given how quickly the tools are changing, it seems better to study this deliberately than to wait and see what folklore develops.

The folks we spoke with showed that people do get there: with enough passes through the materials and enough code written, it eventually clicks. The opportunities above are mostly about making it work for the people who didn't pick Rust on purpose, and for the ones who would have stuck around if their early experience had gone a little differently.

The Rust Programming Language Blog: crates.io: development update

Sat, 25 Jul 2026 08:37:18 +0200

Another six months have passed since our last development update, and the crates.io team has been busy. Here's a summary of the most notable changes and improvements made to crates.io since then.

Source Code Viewer

Crate pages now have a "Code" tab that lets you browse the contents of published crate versions directly on crates.io. This shows you the exact files that cargo downloads when you add a crate as a dependency, which might differ from the linked repository. This makes it much easier to audit your dependencies, including files that never appear in the repository, like the normalized Cargo.toml files that cargo generates.

The viewer comes with a file tree sidebar with search functionality, syntax highlighting, and GitHub-style line selection, where clicking or dragging line numbers produces shareable #L10-L20 URLs.

Under the hood, the server now builds a zip file for every published version. Since the .crate files that cargo consumes are gzipped tarballs without random access support, a background job re-packs each of them into a seekable zip archive plus a JSON manifest describing the contained files. Both are served from our static CDN. The frontend then fetches only the manifest and loads each file on demand with an HTTP range request. Because of this architecture, browsing crate sources essentially adds no load on the crates.io API servers. Existing crate versions have been backfilled, so this works for old releases too.

The rendering library behind the code viewer is a diff renderer at heart, and that's no accident: a version-to-version diff viewer built on the same infrastructure is currently in the works. This will allow you to review exactly what changed between two published versions, right on crates.io. Stay tuned!

Untangling crates.io Accounts from GitHub

At the end of May, the crates.io team accepted RFC #3946. Crates.io accounts always have been tightly coupled to GitHub: signing in means "Log in with GitHub", and your crates.io identity is your GitHub username. The RFC changes that. It introduces usernames that are native to crates.io and independent of linked GitHub accounts, as a prerequisite for eventually supporting login via other identity providers.

The implementation of crates.io usernames has started, but there is still a lot left to do, most visibly the ability to change your crates.io username. After that is complete, there will be future RFCs and implementation for signing in with identity providers other than GitHub. Since all of this touches authentication and account security, we are deliberately taking it slow and rolling these changes out in small, carefully reviewed steps.

Advisories and Suggestions

In our January update we introduced the "Security" tab, which shows security advisories from the RustSec database. We have since taken this integration one step further: crates that RustSec has flagged as unmaintained now show a warning banner directly on their crate pages, linking to the corresponding advisory for details and possible alternatives. Thanks to Dirkjan Ochtman for implementing this feature!

Related to this, some popular crates have been largely absorbed into the Rust standard library over the years, like lazy_static, which has been superseded by std::sync::LazyLock since Rust 1.80. Crate pages of such crates now show a friendly "You might not need this dependency" banner describing the standard library replacement, and superseded crates in dependency lists get a small light bulb icon with a similar hint.

The dataset behind this feature lives in the new rust-lang/std-replacement-data repository, together with a documented inclusion policy: standard library replacements only, every entry must cite the stable std, core, or alloc API and Rust version, and crate maintainers get a notice-and-comment window before an entry is added. New entries can be proposed upstream and can benefit other tools too.

Ferris

The most delightful change of this cycle: the Ferris on our error pages now follows your mouse cursor with its eyes:

Getting a 404 error on crates.io is now slightly less sad.

Svelte Frontend Migration Completed

In our January update, we announced that we were experimenting with porting the crates.io frontend from Ember.js to Svelte. This experiment has concluded successfully: the new frontend reached feature parity, went through a public testing phase in April, became the default at the beginning of May, and the Ember.js app has been removed from our repository.

We designed this change to be invisible for our users, since the new frontend is a 1:1 port of the previous design and functionality. For the team and our contributors, however, it is a big deal: the frontend is now built on a more modern framework, which should make it easier for new contributors to get started. It also allows us to iterate faster, as the source code viewer above demonstrates.

We want to thank the Ember.js team for a framework that served crates.io well for many years, and the Svelte team for making the transition so enjoyable.

Miscellaneous

These were some of the more visible changes to crates.io over the past six months, but a lot has happened "under the hood" as well:

Search performance: Relevance-sorted search queries previously ranked every crate matching the query, which could take 1-2 seconds for short or common search terms. Ranking is now bounded to the 1,000 matching crates with the highest recent download counts.
Reverse dependencies performance: The reverse dependencies endpoint no longer recomputes the full dependent set on every request. It is now served from a precomputed table kept in sync by database triggers, turning an expensive join into a bounded index scan and greatly reducing the chance of getting a timeout error.
New ARCHITECTURE.md: If you've ever wondered how crates.io actually works, our ARCHITECTURE.md document got a complete rewrite. It is now organized around the high-level systems that make up crates.io and how they fit together, and includes walkthroughs of what happens when you run cargo publish, why a typical crate download never touches our API servers, and how download counts are derived from CDN access logs.
Definition lists: READMEs now render Markdown definition lists, a widely used Markdown extension. Our markdown renderer comrak already supported them, the extension just wasn't enabled yet. Thanks to @mistaste for this contribution!
CDN cache tags: Files uploaded to our static CDN now carry cache-tag metadata, allowing us to invalidate all cached files of a crate or a specific release in a single operation, instead of issuing one invalidation per file URL.
Caching improvements: We removed a global Vary: Cookie response header that was preventing our CDNs from caching public API responses and frontend assets effectively. Per-user responses now use Cache-Control: no-store instead, resulting in better cache hit rates at the CDN edge.
Accessibility: We have made crates.io friendlier to screen readers: decorative icons are now hidden from the accessibility tree, heading hierarchies have been fixed, and lists are marked up as proper lists. ARIA snapshot tests now ensure that regressions can't slip in unnoticed. We plan to continue to improve crates.io accessibility over the coming months.
Git index performance: The background worker's local clone of the git index is now a bare and shallow repository, eliminating roughly 250,000 checked-out files and the full commit history from its disk, improving its performance as we see increased rates of crate publication. The periodic index squashing now goes through the GitHub API instead of generating large git packs locally, which had previously caused out-of-memory failures on the production worker.

Feedback

We hope you enjoyed this update on the development of crates.io. If you have any feedback or questions, please let us know on Zulip or GitHub. We are always happy to hear from you and are looking forward to your feedback!

Why Gaming on Linux Suddenly Matters

Sat, 25 Jul 2026 08:36:39 +0200

Author: Techquickie - Bewertung: 24191x - Views:665011

Click this link https://boot.dev/?promo=TECHQUICKIE and use my code TECHQUICKIE to get 25% off your first payment for boot.dev. Thank you Boot.Dev for Sponsoring!

From broken drivers to the Steam Deck selling millions, Linux gaming has gone from "is this the year?" to "wait, it actually works now." But getting here took a decade of tinkering, a billion-dollar bet from Valve, and an open-source community that refused to quit. In this video we talk to Valve and the Batocera project about how Linux quietly became a real threat to Windows - and why Microsoft is playing catch-up.

Leave a reply with your requests for future episodes.

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Purchases made through some store links may provide some compensation to Linus Media Group. Affiliate links powered in part by https://affilimate.com/

Linus Sebastian is an investor in Framework Computer, Inc and HexOS by Eshtek.

Chapters
------------------------------------
0:01 Is this the year of Linux gaming?
0:43 Why Microsoft is usually better
2:03 How Valve is fighting back
3:37 Sponsor
4:14 Steamdeck saved the day
4:50 Windows claps back
6:27 Valve is putting up a fight
7:40 Watch another video

AI Agents as "Games Masters"? 🎮🔥

Sat, 25 Jul 2026 08:36:30 +0200

Author: Two Minute Papers - Bewertung: 150x - Views:17300

Check the pinned comment for the link to the full interview. Could AI agents eventually become the "Games Master" driving your gaming storylines? We explore the concept of AI assisting players or creating dynamic, non-scripted narratives. Discover how AI is currently being tested inside immersive game environments to change how we play. 🧠
Hashtags: #aiingames #gaming #ai #gamedev #futuretech

Valve, was habt ihr euch dabei gedacht?! Steam Machine für 1039 €

Sat, 25 Jul 2026 08:36:15 +0200

Author: PC-WELT - Bewertung: 250x - Views:8464

Wir müssen zurückrudern. 😅

Wir haben die Steam Machine vor ein paar Wochen noch verteidigt, aber nach dem Preis-Leak wird’s schwierig.

Die Idee bleibt stark: keine Online-Abos, günstige Steam-Spiele, Zugriff auf die eigene Steam-Bibliothek und Cloud-Saves zwischen PC und Konsole.

Aber: Die Basis-Version soll 1039 € kosten. Für eine Konsole, die teils langsamer ist als eine deutlich günstigere PS5, ist das schwer zu rechtfertigen.

Valve hat beim Preis unserer Meinung nach komplett übers Ziel hinausgeschossen.

Was meint ihr: verkalkuliert oder trotzdem ein Erfolg? 👇
-
#SteamMachine #Valve #GamingNews #SteamDeck #GamingCommunity

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Das HMX-6-LOGO ist da! 😱

Sat, 25 Jul 2026 08:36:12 +0200

Author: PC-WELT - Bewertung: 200x - Views:6601

Das fetteste Gaming-PC-Gewinnspiel geht wieder los! 🥳 Und ... das HMX-6-LOGO ist da! 🤩

Chef, wenn du das hier siehst: Sorry, war zu gehyped. 🥲

👉 So machst du beim Gewinnspiel mit:
https://www.pcwelt.de/3179491

👉 Alle Infos zur HMX 6:
https://www.pcwelt.de/hmx

Alle Infos findest du auch über den Link in der Bio.

VIEL GLÜCK! 🍀
-
#hmх6

Die HMX 6 ruft an ✌️ #gewinnspiel

Sat, 25 Jul 2026 08:36:11 +0200

Author: PC-WELT - Bewertung: 95x - Views:5433

Ja hallo? Oh, nice! Es gibt wieder etwas zu gewinnen! Und zwar den brutalsten Gaming-PC des Jahres: die HMX 6!

Und das Ganze ohne Kontozwang! 👍

Du machst noch nicht mit? Na dann wird’s Zeit!

👉 So machst du beim Gewinnspiel mit:
https://www.pcwelt.de/3179491

👉 Alle Infos zur HMX 6:
https://www.pcwelt.de/hmx

Alle Infos findest du auch über den Link in der Bio.

VIEL GLÜCK! 🍀
---
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Ich teste die GTX 1080 Ti in 2026 – und bin überrascht!

Sat, 25 Jul 2026 08:36:07 +0200

Author: PC-WELT - Bewertung: 567x - Views:55426

Die GTX 1080 Ti war keine normale Grafikkarte - schon bei ihrem Erscheinen war klar: Das ist was besonderes. Günstiger UND schneller als das absolute Spitzenmodell Titan X, üppig ausgestattet, pure Rechenpower. Kein Wunder, dass die 1080 Ti heute immer noch gefeiert wird.

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0:00 Intro
1:33 SO gut war die 1080 Ti! (und so günstig)
5:35 Cyberpunk 2077 Benchmark
7:16 Hogwarts Legacy Benchmark
9:30 CS:GO Benchmark
10:59 Gesamt-Performance, Preis & Fazit

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Linux-Gaming 2026: Ist Bazzite besser als Windows?

Sat, 25 Jul 2026 08:36:04 +0200

Author: PC-WELT - Bewertung: 347x - Views:9175

Gaming unter Linux? Ich dachte: Gefrickel, Treiber-Hölle und am Ende doch wieder Windows.

Nach einer Woche mit Bazzite auf meinem Gaming-PC lag ich ziemlich daneben.

Bazzite ist eine Linux-Version für Gaming: Steam, Controller-Support und GPU-Treiber sind direkt vorbereitet. Viele Windows-Spiele laufen dank Proton überraschend problemlos.

Wichtig vor dem Download: Check dein Spiel auf ProtonDB. Dort siehst du, ob es läuft und welche Proton-Version empfohlen wird.

PC-WELT-Check: Linux-Gaming ist nicht mehr nur was für Bastler – vor allem, wenn du hauptsächlich über Steam zockst. Bei Epic, GOG & Co. wird es mit Tools wie Lutris oder Heroic etwas hakeliger.

Zockst du schon mit Linux?
-
#Steam #GamingPC #PCGaming #Linux

Why The Fastest Memory Isn't In Your PC (HBM explained)

Sat, 25 Jul 2026 08:35:58 +0200

Author: Techquickie - Bewertung: 4552x - Views:77047

Thanks to Micron for sponsoring this video!

To learn more about High-Bandwidth Memory (HBM), check out: https://www.micron.com/products/memory/hbm

Interested in helping to shape the future of cutting edge memory and storage: https://www.micron.com/about/careers

Modern AI chips don't run on the kind of memory in your gaming PC. They run on something that's literally stacked into a tiny skyscraper, with tens of thousands of microscopic data tunnels drilled through it and a custom silicon motherboard underneath. We sat down with the engineers at Micron to break down how High Bandwidth Memory actually works, why it's the backbone of every serious AI accelerator on the planet, and why your gaming GPU still uses a totally different kind of memory.

Leave a reply with your requests for future episodes.

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Ich brauche Windows nicht mehr! Bazzite vs. CachyOS

Sat, 25 Jul 2026 08:35:50 +0200

Author: PC-WELT - Bewertung: 1109x - Views:21055

Gaming auf Linux war lange kompliziert oder scheiterte gleich am Game-Support. Doch die Zeiten sind vorbei - dank Distros wie Bazzite oder CachyOS macht Zocken auf Linux mittlerweile richtig Bock. Doch welche Gaming-Distro ist die beste? Was sind die Unterschiede zwischen Bazzite und CachyOS? Das hab ich mir mal genauer angeschaut.

► https://youtu.be/Zz-qL5JRm4s

► https://youtu.be/j0pM0S3wmbc

► https://www.youtube.com/watch?v=mVXONaHZvFU

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0:00 – Intro: Ist Linux-Gaming 2026 die bessere Wahl?
0:52 – Was ist CachyOS? (Arch Linux & Rolling Releases)
1:29 – Warum CachyOS schneller läuft (CPU-Optimierung & Compiler-Standards)
2:57 – Installation & Dual-Boot im Vergleich
3:38 – Anpassbarkeit: Desktops & Bootloader
3:59 – Systemsicherheit: Die "Atomic Updates" von Bazzite
4:32 – Software-Quellen: CachyOS (Pacman & AUR) vs. Bazzite (Flatpaks)
5:46 – Out-of-the-Box: Wer ist schneller spielbereit?
6:36 – Spiele-Performance & das Nvidia-Treiber-Problem unter Linux
7:01 – Fazit: Welches OS ist besser für dich?
7:39 – Handheld-Gaming (Steam Deck & Co.): Bazzite weiterhin vorn?
8:15 – Outro

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Ist die GTX 1080 Ti die beste Grafikkarte aller Zeiten?

Sat, 25 Jul 2026 08:35:40 +0200

Author: PC-WELT - Bewertung: 484x - Views:13584

Beste Grafikkarte aller Zeiten? 👑

Die NVIDIA GeForce GTX 1080 Ti kam 2017 für 819 € – mit 11 GB VRAM, 3.584 CUDA-Kernen und mehr Leistung als die teurere Titan X. Fast 10 Jahre später läuft die Pascal-Legende noch erstaunlich gut in 1080p: kein DLSS, kein Raytracing – einfach rohe GPU-Power.

Welche Grafikkarte verdient für dich Legendenstatus? 👇
-
#GTX1080Ti #NVIDIA #Grafikkarte #PCGaming #gaminghardware

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Was ist das?? | HMX 6 Casemod

Sat, 25 Jul 2026 08:35:33 +0200

Author: PC-WELT - Bewertung: 142x - Views:4522

Was baut Stefan von @RandomDesign hier für unsere HMX 6? 👀🎮

Schreib deinen Guess in die Kommentare – mal sehen, wer richtig liegt! 🔥

Du willst den Halo-Tisch-PC gewinnen?

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👉 Alle Infos zur HMX 6:
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Alle Infos findest du auch über den Link in der Bio. Und wie immer: ohne Kontozwang!

VIEL GLÜCK! 🍀

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Wie alles begann: Die wahre Geschichte der Höllenmaschine

Sat, 25 Jul 2026 08:35:30 +0200

Author: PC-WELT - Bewertung: 870x - Views:15601

20 Jahre ist die Höllenmaschine nun schon alt - 20 Jahre voller krasser Hardware, verrückten Geschichten und jeder Menge Katastrophen. Aber auch eine Zeit, die unglaublich viel Spaß gemacht hat und uns mit vielen besonderen Menschen zusammen gebracht hat. Zum großen Jubiläum der Höllenmaschine schauen wir noch mal zurück, wie es überhaupt zum Projekt Höllenmaschine kam, welche Pannen es gab und was wir uns eigentlich dabei gedacht haben.

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0:00 Intro
1:15 Höllenmaschine 1
9:27 Höllenmaschine 2
13:32 Höllenmaschine 3
18:31 Höllenmaschine 4
30:08 Höllenmaschine 5
37:52 Höllenmaschine 6
47:52 Höllenmaschine 7
57:43 Höllenmaschine UVR
1:10:55 Höllenmaschine 8

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OLED vs. IPS vs. VA: Welcher Gaming-Monitor ist wirklich der beste?

Sat, 25 Jul 2026 08:35:25 +0200

Author: PC-WELT - Bewertung: 201x - Views:4976

TN, VA, IPS, Mini-LED oder OLED – welche Display-Technik ist fürs Gaming wirklich die beste? 🎮 IPS ist der starke Allrounder, Mini-LED die Premium-LCD-Lösung und OLED liefert die beste Bildqualität. Welches Panel nutzt ihr aktuell – und würdet ihr es wieder kaufen? 👇

#GamingMonitor #OLEDGaming #MiniLED #PCGaming #MonitorTipps

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Gaming-PC startet nicht? Diese kleine Schraube könnte schuld sein

Sat, 25 Jul 2026 08:35:21 +0200

Author: PC-WELT - Bewertung: 43x - Views:1588

Diese kleine Schraube kann deinen ganzen Gaming-PC killen.

Speicher dir das, bevor du deinen ersten PC zusammenbaust.
-
#GamingPC #PCBuild #PCGaming #HardwareTipps #Mainboard

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Windows-10-Ende: Linux-Anbieter jubelt über Rekord-Downloads

Sat, 25 Jul 2026 08:23:22 +0200

Der Umstieg von Windows auf Linux gilt unter vielen Nutzern noch immer als großer Schritt. Immer mehr Anwender sind aufgrund des Windows-10-Endes inzwischen aber zu diesem bereit, da die Alternative wohl im Kauf neuer Hardware bestehen würde. (Weiter lesen)

Nvidia GeForce Download - Windows 10/11 Grafik-Treiber

Sat, 25 Jul 2026 07:42:00 +0200

Der Download installiert die neuesten Nvidia Treiber für GeForce-Grafikkarten unter Windows 10/11 und garantiert so eine optimale Performance in Spielen. (Weiter lesen)

‘I thought, I’ve tried everything else, why not give AI a shot?’: the long-lost family reunited by ChatGPT

Sat, 25 Jul 2026 07:28:08 +0200

MacBook Neo’s success wasn’t luck, it was a plan

Sat, 25 Jul 2026 06:47:11 +0200

It’s difficult to ignore the fact that Apple seems to have turned its MacBook Neo into a weapon to promote platform growth, with enough performance under the hood to make competitors seem inferior.

And even as the PC industry moves to try to compete with Apple’s last huge Mac success, the company is already planning a powerful follow-up.

That points to the discipline Apple has applied to the Mac since the introduction of Apple Silicon. The company has built a clear product roadmap, strong entry-level pricing, and steady performance gains. This focus is now paying dividends, giving people the impetus to keep placing their trust in Apple and its Macs — even as the industry raises prices in the face of RAMageddon and price increases.

The numbers don’t lie

“Apple’s recent price increase seems to be an inevitable response to these cost increases. In the second half of the year, other PC OEMs are expected to continue to raise prices, and the overall ASP increase is expected to continue,” Counterpoint said in a post Wednesday. The researcher tells us global PC shipments shrank 4% in the second quarter of 2026 as rising costs hit demand. The Mac maker, by contrast, moved in the opposite direction, generating 13% growth in the quarter — mainly on the back of the MacBook Neo introduction.

Recent IDC data gives Apple 10.1% year-over-year growth and just under 10% (9.9% to be exact) of the worldwide PC market, even as the overall market declined 4.9%.

“With emerging supply chain and tariff challenges inflating memory prices…, Apple’s incredibly aggressive price-point for the MacBook Neo makes its release feel all the more like a gut punch to one of the PC market’s most valuable price tiers,” Futurum Research Director Olivier Blanchard said when the Neo was released.

Neo 2.0 is already coming

In the immediate future, as competitors raise prices on the PCs that compete with Apple’s lower-cost device, Cupertino is already plotting the path toward MacBook Neo 2. Reports claim this will debut in March in new colors and use the A19 Pro chip from the iPhone 17 Pro, with performance boosted by slightly more unified memory (12GB, rather than 8GB). That’ll make it a much better Mac, likely with 10-15% performance gains and the ability to run Apple Intelligence, making it the best and most affordable AI PC in its class.

Just four months after the Neo’s rollout, Apple is already in position to leak rumors of an even more computationally capable follow-up, while competitors struggle to compete with the original on performance, build quality, and price. Still, the Neo might get more expensive, reporting warns, with the lowest-price 256GB model now gone, making the $599 Mac a mirage we can only wistfully hope to see again.

That might matter less in context, as PC makers everywhere boost prices while RAM, chips, and storage prices head north, along with transport, logistics, and energy costs. “While [Apple] did raise prices in line with the broader market, it still remains well positioned against rivals facing the same cost pressures,” said Jean Philippe Bouchard, vice president for consumer devices at IDC.

“As market conditions continue to worsen, the importance of supply chain management and capabilities are increasingly important,” Bouchard said. “The largest vendors, with their buying power and long-standing supplier ties, are best positioned to take share from smaller rivals.”

This was never about luck

This isn’t solely a market take about competition, it’s about planning.

Few in the industry seemed prepared for the massive memory price increases that hit this year. Apple clearly planned its low-cost Mac well before that happened, hoping to seize the PC market at the low-mid-range. This is precisely what it seems to have done, what it continues to do, and what it will continue to do.

The recent reports that it has a successor planned shows the breadth of the Mac company’s strategic vision, as Apple has quite clearly sought to fully exploit the failings of Windows and the internal contradictions of a value-conscious industry in stiff competition with itself.

With the first M-series Macs about to enter the replacement cycle, Apple has built a market it can capitalize on for at least a decade, meaning it already has a vision for PC sales that extends at least as far. That’s the kind of road map corporate purchasers want when they make platform deployment decisions, which is why Apple’s 10% share gains are the beginning of even more significant market change.

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CIOs beware: DNS KSK rollover could kick off wave of mysterious outages

Sat, 25 Jul 2026 06:16:22 +0200

Predicting an outage is tricky business, but CIOs might want to circle Oct. 11, 2026, through Jan. 11, 2027, for likely trouble of a potentially widespread and puzzling nature.

That’s because a relatively trivial update to DNSSEC on Oct. 11, one that will take full effect by Jan. 11, is likely to deliver a series of seemingly unrelated system outages. This will come from oceans of dependencies from third-party, shadow, agentic, gen AI, SaaS, homegrown, and legacy apps — among many other quiet executable hiding spots, including virtual environments and containers.

Sai Joshitha Kathari, senior site reliability engineer at payment card giant Visa, says most enterprises have far more DNS-related exposure than they realize because of these many dependencies.

“This has the potential to create real downstream destruction when unresolved failures sit underneath important business functions,” Kathari says.

The danger is that so many of these issues are either unknown to IT or handled by a third-party vendor and no one in IT has had reason to ask those vendors about DNS updates.

“The risky areas are usually not the obvious managed DNS services. They are the older internal applications, hardcoded resolvers, containerized workloads, sidecar configurations, custom scripts, partner integrations, VM images, stale base images, and service-to-service dependencies that nobody has touched in a long time,” Kathari explains. “These systems can keep working quietly for years, then fail during a DNS or certificate-related change because they bypassed the normal platform standards.”

Independent technology analyst Carmi Levy says that CIOs need to take this event very seriously.

“The two-pronged deadline — October 11, 2026, when the new Key Signing Key (KSK) begins signing the root zone, and January 11, 2027, when the old key is retired — should be marked in red on everyone’s calendar, just as December 31, 1999, once was,” Levy says. “Failure to comply could result in websites, critical business applications, and related resources dropping off the face of the Earth once the transition is complete.”

Levy adds: “Custom-built code that lives outside conventional support mechanisms may or may not function when the DNS changes go into effect.”

The DNSSEC update itself is straightforward, but it is also the first significant DNSSEC change — specifically a change in the trust anchor — since 2018.

The rollout statement noted that “the trust anchor is formally known as the Domain Name System Security Extensions (DNSSEC) root zone Key Signing Key (KSK). The KSK is the cryptographic key at the core of the DNSSEC trust anchor and is used to verify that DNS responses are legitimate and have not been modified in transit.”

Expect nearly every enterprise to be impacted

Kim Davies, vice president of IANA Services and president of public technical identifiers at ICANN, says the extent of the impact on enterprises is unknowable, given the nature of shadow IT and other edge cases.

But based on the massive number of dependencies both known and unknown in the typical global enterprise, Davies guesses that just about every enterprise will be impacted, to varying degrees.

“In highly complex organizations, it is very likely there will be some impact in the corners, in the margins, of the organization,” Davies tells CIO. “DNS is such a core technology that underpins everything.”

As the updates propagate, hiccups will materialize, Davies notes. “When the system cannot validate the [DNS] information, it will treat it as suspect and DNS lookups will fail.”

Visa’s Kathari says, “Enterprises should expect some secondary DNS-related glitches when major DNSSEC-related changes happen, not necessarily because the core infrastructure teams will ignore the update, but because large environments have many hidden dependency paths.”

Making this problem far worse, Kathari notes, is that the glitches will likely initially look like anything other thana DNS glitch. That will force IT staff to waste a vast number of hours chasing causes that ultimately prove to be unrelated to the incidents.

“The impact for CIOs is that DNS failures rarely announce themselves as DNS failures. They look like application timeouts, broken logins, failed API calls, queue lag, payment failures, partner connectivity issues, or random regional instability,” Kathari explains. “That makes troubleshooting slower because teams may spend hours looking at the application, database, network, or cloud provider before realizing name resolution is part of the failure path.”

Sanchit Vir Gogia, chief analyst at Greyhound Research, agrees that IT will likely spin its wheels chasing the wrong ghosts.

“A validation failure rarely stays in its lane. It surfaces as an application error, an API timeout, or a reachability problem, which turns a resolver fault into a coordination failure,” Gogia says. “The application team blames the network, the network team blames the cloud, and the user simply watches work stop.”

“Images and templates are the frontier most teams miss,” Gogia adds. “A resolver fixed in summer can be broken again in October the instant a stale golden image is redeployed, because automation no longer lets configuration drift slowly. It restores yesterday’s assumptions at machine speed.”

It is widely expected that enterprises will not have any problems executing the change or, more likely, relying on their hyperscalers to properly handle the change. That is the concern.

“CIOs are being distracted so much with AI and this is such a deep in the weeds infrastructure issue that this can and willcatch people off-guard,” Justin Greis, CEO of consulting firm Acceligence, tells CIO. “I think we’ll see a meaningful number of enterprise disruptions associated with the DNSSEC trust anchor rollover. Not because the update itself is especially difficult, but because it will expose weaknesses that already exist inside many organizations.”

Most enterprise IT operations have had no reason to compile a comprehensive list of all DNS dependencies, but many will be instantly discovered in January.

Potentially widespread fallout

A major retailer, for example, might suddenly be unable to connect with FedEx to arrange for deliveries or a hospital may find that test results are no longer being shared with patient portals. It might manifest as an assembly line that halts because an IIoT component can no longer share files with its vendor system or a truck fleet that stops being tracked.

“There will almost certainly be systems that fall through the cracks. Some will be legacy applications that rely on outdated DNS configurations that have not been updated in years,” Greis says. “Others will be business-unit-developed tools, contractor-built solutions, embedded systems, manufacturing and industrial systems, or highly customized workloads that operate outside normal IT oversight. These are the types of systems that often surface during infrastructure events like this.”

Greis adds that many enterprises will discover in January problems created by their own automation.

“Over time, enterprises build layers of processes, templates, and deployment mechanisms that are reused across teams and environments,” Greis notes. “Even after DNS infrastructure is updated correctly, older settings can inadvertently be reintroduced through routine updates and system changes, creating intermittent and difficult-to-diagnose failures.”

The good news from this situation is that enterprises are not going to likely lose all DNS access if any of these glitches occur. But that may be of no comfort because even if the disruptions are only with small edge cases, that can still cause massive operational disruptions.

Cricket Liu, EVP and chief evangelist at Infoblox, gives the example of a DNS server that responds to factory-floor system queries.

“Or let’s say this disrupts [an enterprise’s key] SaaS application. All name resolution may stop and it will show a server failure. It will not deliver a response whenever I look anything up. That’s not subtle at all,” Liu says. “It’s highly likely that companies are going to see some effects.”

Back in 2017, the switchover was relatively uneventful, giving some CIOs hope that January 2027 will also be a non-event. But given the technology advancements in the last 10 years and the resulting tidal wave of new enterprise tech dependencies, few are realistically expecting no problems this go around.

Impossible to predict what will happen

One of the top network experts on DNS effects in enterprises is Geoff Huston, chief scientist at the Asia Pacific Network Information Centre (APNIC), the regional Internet Registry administering IP addresses for the Asia Pacific region.

Huston says it is difficult to project what will happen in January until it happens.

“Just like the last time, we are flying blind with this key roll. Because nothing really terrible happened last time, there is some confidence that nothing terrible will happen this time, but we just can’t tell in advance as there are no good measurement approaches that allow us to peek inside the trust state of recursive resolvers,” he says.

As for potential edge-case glitches, Huston says it is possible, but if third-party vendors do not properly handle the update, there will be other issues as well, as the KSK cryptographic key used within DNSSEC signs and validates the keys that protect DNS records.

“If it is not standards-compliant, then you have more problems than just the KSK roll,” Huston says, “as it raises the obvious question of ‘What else is not correctly implemented in the DNS resolver that I’m running?’”

As a silver lining, Acceligence’s Greis says any hiccups that result from the DNS KSK update may be a gift in disguise for CIOs.

“The irony is that some of the most business-critical components in the technology stack are often the least visible because they work in the background,” Greis says. January “may reveal how much modern business resilience depends on infrastructure that many organizations rarely examine until something breaks. For CIOs, that’s the real lesson. This is not fundamentally a story about a DNS update. It is a story about operational visibility, resilience, and governance. Organizations that treat the rollover as a routine infrastructure task will likely complete the update and move on. Organizations that use it as an opportunity to understand and strengthen the foundations of their technology environment may gain far more value than simply avoiding an outage.”

5 endpoint blind spots your EDR/XDR was never built to see

Sat, 25 Jul 2026 00:18:11 +0200

In August 2025, 126 malicious packages landed in the npm registry. Even after the community caught the initial wave, 80 of these hidden backdoors remained actively listed.

#1. Gain real-time visibility into shadow AI & extensions

#2. Distinguish between human and autonomous agent behavior

#3. Establish guardrails for automated package updates on endpoints

#4. Enforce principle of least privilege for AI agents

#5. Maintain continuous endpoint posture management

Summary

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Philips Evnia 32M2N6901A: QD-OLED-Gaming-Monitor und AmbiScape-Unterstützung kommt mit 165 Hz

Fri, 24 Jul 2026 23:17:49 +0200

Neben dem Philips Evnia 32M2N8900P hat das Unternehmen MMD, welches hinter der Marke Philips im Monitor-Bereich steckt, einen weiteren QD-OLED-Bildschirm zum Zocken vorgestellt: den Philips Evnia 32M2N6901A....

Zum Beitrag: Philips Evnia 32M2N6901A: QD-OLED-Gaming-Monitor und AmbiScape-Unterstützung kommt mit 165 Hz

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Simon Willison Breaks Down OpenAI’s Sandbox Escape Incident

Fri, 24 Jul 2026 21:03:04 +0200

An OpenAI model being tested for cybersecurity capabilities decided to cheat rather than solve its assigned test, breaking out of its sandbox and hacking into Hugging Face to steal the answers. Simon Willison calls it “science fiction that happened.”

Read original article

In Schwarz oder Weiß: QD-OLED-Monitor ASRock PGO27QSA erreicht den Markt

Fri, 24 Jul 2026 21:02:13 +0200

Der zur CES von ASRock angekündigte OLED-Monitor Phantom Gaming PGO27QSA erreicht den Markt. Den 27"-Monitor mit 2.560 × 1.440 Pixeln und 240 Hz gibt es in Schwarz oder Weiß zu kaufen. Der Preis liegt bei unter 500 Euro und ist damit vergleichsweise hoch.

‘Lucky’ Season 1 Episode 3 Recap: Lucky Finally Tracks Down Cary

Fri, 24 Jul 2026 20:27:30 +0200

“Lucky” Season 1, Episode 3 follows Lucky as she searches for Cary and the stolen money, using every trick she learned during her unusual childhood. The episode, titled “Read the Room,” also reveals that Agent Billie Rand’s pursuit of Priscilla has become deeply personal. “Lucky” is a seven-episode Apple TV limited series based on Marissa Stapley’s novel. The first two episodes arrived on July 15, followed by weekly releases through August 19. Episode title: Read the Room Release date: July 22, 2026 Runtime: 45 minutes Spoiler warning for “Lucky” Episode 3 After the failed multimillion-dollar robbery, Lucky remains separated from Cary, who disappeared with their money. She also continues running from Priscilla’s people and the FBI while relying on the criminal skills taught to her by her father, John. Episode 3 begins with a flashback showing John completing a deal for Priscilla as Agent Rand watches nearby. Lucky warns John that the situation will end badly. In the present, Rand follows Lucky’s trail through gas-station security footage, although she remains several steps behind her. Lucky reaches Priscilla’s farm and hides while Dutch questions Noah about fake identification documents. Dutch eventually kills him, allowing Lucky to steal Noah’s identification and search for the person making the fake documents. Lucky crashes a child’s birthday party Before continuing her search, Lucky enters a child’s birthday party to obtain clothes, money and transportation. A flashback shows John teaching young Lucky how to steal at such events, including taking cash envelopes and unattended purses. Lucky leaves the party with a new outfit, enough money to tip a valet and someone else’s car. The scene shows how easily she can enter an unfamiliar environment, gain people’s trust and disappear before anyone notices what happened. At Noah’s home, Lucky discovers that his neighbour creates fake IDs. While studying her previous work, Lucky finds evidence that Cary used her services and adopted the name Colson Smith. Lucky finally finds Cary Lucky manipulates a real-estate agent into giving her access to the property where Cary is staying. While Cary swims nearby, she searches the house and discovers a gun and a laptop protected by a 12-word seed phrase. Cary returns to find the property destroyed and Lucky waiting inside. Meanwhile, Wayne tells Priscilla that he has also discovered Cary’s location, placing both Cary and Lucky in immediate danger. Episode 3 ends with the former partners finally reunited, although their missing money and broken trust remain unresolved. What do you think Cary will tell Lucky, and will they work together against Priscilla? Let us know in the comments.

99 % Raubkopierer: Anti-Piraterie-Gag sorgt für Verkaufsexplosion

Fri, 24 Jul 2026 19:51:10 +0200

99 % Raubkopierer: Ein Indie-Entwickler wird mit einem Anti-Piraterie-Gag viral – bis die Realität ihn einholt.

Der Artikel 99 % Raubkopierer: Anti-Piraterie-Gag sorgt für Verkaufsexplosion erschien zuerst auf TARNKAPPE.INFO

'Science fiction that happened': experts explain why OpenAI's 'mind-blowing' cyberattack should worry us all

Fri, 24 Jul 2026 17:38:38 +0200

This might be our first true glimpse of how dangerous AI could be in the future in terms of making hacks much more commonplace.

Wer soll das bezahlen? Nvidias RTX-Karten droht nächste Preiserhöhung

Fri, 24 Jul 2026 16:28:08 +0200

Käufer von GeForce-Grafikkarten müssen sich womöglich erneut auf steigende Preise einstellen. So verlangt Nvidia von seinen Produktionspartnern künftig angeblich mehr Geld für seine GPU-Kits. Betroffen sind wohl aktuelle und kommende RTX-Modelle. (Weiter lesen)

I’ve been gaming for 40 years. Here are the best chairs in the UK for comfort, support and serious play

Fri, 24 Jul 2026 16:21:24 +0200

Whether you’re on PC or a console, level up your setup with our gaming expert’s pick of the best chairs

• The best games of 2026 so far

Comfort is crucial to the gaming experience. It’s hard to focus on blasting aliens or taking Stoke to the Champions League final if your bum has gone to sleep because you’ve been sitting on an old chair for three hours. We’re spending more time playing games than ever before, so good posture matters. If you have set up a dedicated gaming space, then a rickety seat just won’t cut it.

From luxurious ergonomic thrones to cheap-and-cheerful bucket seats, the options available are bewildering. So I set out on an epic quest: to find the most comfortable, durable and stylish gaming chairs. Here’s what I discovered.

Best gaming chair overall:
Secretlab Titan Evo

Best budget gaming chair:
ThunderX3 Solo 360

4K-Mini-LED trifft auf GeForce RTX 5090 Laptop - Asus ROG Strix SCAR 18 G835LXG im Test

Fri, 24 Jul 2026 16:21:16 +0200

World of Warcraft: Admin nutzt Cheat für Freunde - Fristlose Kündigung

Fri, 24 Jul 2026 16:04:36 +0200

In World of Warcraft (WoW) hat ein Game Master seine weitreichenden Rechte missbraucht, um Freunden in einem anspruchsvollen Dungeon einen unfairen Vorteil zu verschaffen. Der Vorfall flog auf und zog nun drastische Konsequenzen nach sich. (Weiter lesen)

LG 27GX790B-B im Test: Tempo trifft Bildqualität

Fri, 24 Jul 2026 15:57:09 +0200

Der LG 27GX790B-B verspricht Gaming in Höchstgeschwindigkeit. COMPUTER BILD hat Bildqualität, Ausstattung, Stromverbrauch und Ergonomie getestet.

Alienware AW2726DM im Test: OLED-Gaming zum Kampfpreis

Fri, 24 Jul 2026 15:57:07 +0200

Der Alienware AW2726DM gehört zu den günstigsten QD-OLED-Gaming-Monitoren. COMPUTER BILD prüfte, wo seine Stärken und Schwächen liegen.

The biggest indie "friendslop" game of 2026 appears to be delivering malware via Steam Workshop — How to protect your PC (and what to do next)

Fri, 24 Jul 2026 15:04:18 +0200

The Steam Workshop is one of the PC gaming platform's biggest assets, but it's increasingly becoming a place where bad actors can spread malware to unsuspecting victims. The latest allegations involve indie smash-hit Meccha Chameleon. Here's what you need to know.

Alienware 15 review: Perfect timing for a budget gaming laptop

Fri, 24 Jul 2026 14:33:46 +0200

While its display could be nicer, Alienware's first budget gaming laptop feels like a welcome reprieve when practically all tech is more expensive.

Beam Eye Tracker app adds Linux and macOS support in Beta

Fri, 24 Jul 2026 13:05:03 +0200

The highly rated Steam app Beam Eye Tracker just recently released a public Beta for their impressive looking eye-tracking app for gaming.

Read the full article on GamingOnLinux.

Why I changed how I pitch AI: It’s no longer about saving money, but managing tokens and adoption

Fri, 24 Jul 2026 13:04:13 +0200

AI as a leadership multiplier

Integrating AI into the broader business strategy also dictates how we measure success. It forces a shift away from short-term tech vanity metrics and anchors the technology into a long-term roadmap.

The requirement for top-down, executive ownership stems from three critical realities observed in the field:

Silo-smashing and data collaboration: True enterprise AI is data-hungry and that data lives across disparate business lines, finance, operations, marketing and customer service. Only the CEO possesses the cross-functional authority to demand that data silos be dismantled.
Cultural transformation and fear mitigation: AI triggers widespread anxiety over job displacement across all industries and hierarchies. When relegated to an “IT project,” resistance spikes as teams view it as a threat to their livelihoods. When I saw the CEO lead this cultural shift directly is when I noticed the best results.
C-Suite education and strategic alignment: The mandate for AI capability cannot just be delegated downward; the transformation must begin at the very top. I have conducted more than 70 presentations for the Board of Directors and C-Level teams. These people need to be actively educated not on technical code, but on specific business use cases, return on investment (ROI) frameworks and how AI resolves core organizational bottlenecks.

AI as a new operational framework

In terms of cost calculation, we had to teach CIOs and business managers to forget the monthly subscription model for AI and learn to manage the primary unit of exchange in modern AI: the token.

Risks in the AI adoption model

This article is published as part of the Foundry Expert Contributor Network.
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Luna: Amazon baut Cloud-Gaming in Prime Video ein

Fri, 24 Jul 2026 12:49:47 +0200

Filme, Serien und Spiele aus einer App: Amazon integriert seinen Cloud-Gaming-Dienst Luna in Prime Video und macht Gaming damit deutlich sichtbarer. (Prime Video, Amazon)

CIOs beware: DNS KSK rollover could kick off wave of mysterious outages

Fri, 24 Jul 2026 12:09:00 +0200

Predicting an outage is tricky business, but CIOs might want to circle Oct. 11, 2026, through Jan. 11, 2027, for likely trouble of a potentially widespread and puzzling nature.

Sai Joshitha Kathari, senior site reliability engineer at payment card giant Visa, says most enterprises have far more DNS-related exposure than they realize because of these many dependencies.

“This has the potential to create real downstream destruction when unresolved failures sit underneath important business functions,” Kathari says.

The danger is that so many of these issues are either unknown to IT or handled by a third-party vendor and no one in IT has had reason to ask those vendors about DNS updates.

Independent technology analyst Carmi Levy says that CIOs need to take this event very seriously.

Levy adds: “Custom-built code that lives outside conventional support mechanisms may or may not function when the DNS changes go into effect.”

The DNSSEC update itself is straightforward, but it is also the first significant DNSSEC change — specifically a change in the trust anchor — since 2018.

Expect nearly every enterprise to be impacted

But based on the massive number of dependencies both known and unknown in the typical global enterprise, Davies guesses that just about every enterprise will be impacted, to varying degrees.

As the updates propagate, hiccups will materialize, Davies notes. “When the system cannot validate the [DNS] information, it will treat it as suspect and DNS lookups will fail.”

Sanchit Vir Gogia, chief analyst at Greyhound Research, agrees that IT will likely spin its wheels chasing the wrong ghosts.

It is widely expected that enterprises will not have any problems executing the change or, more likely, relying on their hyperscalers to properly handle the change. That is the concern.

Most enterprise IT operations have had no reason to compile a comprehensive list of all DNS dependencies, but many will be instantly discovered in January.

Potentially widespread fallout

Greis adds that many enterprises will discover in January problems created by their own automation.

Cricket Liu, EVP and chief evangelist at Infoblox, gives the example of a DNS server that responds to factory-floor system queries.

Impossible to predict what will happen

Huston says it is difficult to project what will happen in January until it happens.

As a silver lining, Acceligence’s Greis says any hiccups that result from the DNS KSK update may be a gift in disguise for CIOs.

Is last year's Samsung Galaxy Tab S10 FE still worth buying? I multi-screened movies, maxed out gaming graphics, and dunked it in a tank to find out

Fri, 24 Jul 2026 11:35:15 +0200

Samsung’s Galaxy Tab S10 FE not only turned me into a multitasking and note-taking machine; its epic battery life and lush display are perfect for binge watching, too.

Spielestreaming: Xbox testet Cloud Gaming mit Werbung

Fri, 24 Jul 2026 10:50:25 +0200

Microsoft lässt erste Nutzer Xbox-Spiele ohne Cloud-Gaming-Abonnement streamen. Dafür müssen sie vor dem Start Werbung ansehen. (Cloud Gaming, Microsoft)

Gaming mit Werbeunterbrechung: So will Microsoft es jetzt testen

Fri, 24 Jul 2026 10:04:09 +0200

Microsoft testet ein neues Werbemodell für Gamer:innen. Dadurch werden Anzeigen direkt vor der Spielesession angezeigt. Wie das Ganze funktioniert und welche Vorteile Spieler:innen dadurch haben sollen. weiterlesen auf t3n.de

Amazon integriert seinen Gaming-Dienst Luna in Prime Video

Fri, 24 Jul 2026 09:53:42 +0200

Amazon baut Prime Video zu einer umfassenderen Unterhaltungsplattform aus und integriert seinen Cloud-Gaming-Dienst Luna. Deutsche Nutzer werden allerdings noch etwas Geduld mitbringen müssen. (Weiter lesen)

Mehr Sichtbarkeit für das Cloud-Gaming: Amazon beginnt Integration von Luna in Prime Video

Fri, 24 Jul 2026 09:03:32 +0200

Um seinem Cloud-Gamingdienst „Luna“ mehr Sichtbarkeit zu verschaffen, beginnt Amazon mit der Integration in die Prime Video-App. Die USA und Großbritannien machen den Anfang. Eigentlich sollte Cloud-Gaming der ganz große Trend werden, es steckt aber nach wie vor in einer Nische fest. Einzig Nvidia scheint mit GeForce Now fest etabliert. Google hat bereits vor Jahren […]

Der Beitrag Mehr Sichtbarkeit für das Cloud-Gaming: Amazon beginnt Integration von Luna in Prime Video erschien zuerst auf Dr. Windows.

Amazon Prime Video integriert Spiele-Dienst Luna

Fri, 24 Jul 2026 08:15:13 +0200

Wie der Konzern am Donnerstag bekanntgegeben hat, bindet Prime Video künftig auch Videospiele fest in seine Streaming-Plattform ein. Möglich wird das durch die Verschmelzung mit „Luna„, dem hauseigenen Cloud-Gaming-Angebot des Unternehmens. Ab sofort können Besitzerinnen und Besitzer von Fire-TV-Geräten in den USA sowie in Großbritannien direkt loslegen: im Angebot sind unter anderem Titel wie „Hogwarts […]

Der Beitrag Amazon Prime Video integriert Spiele-Dienst Luna erschien zuerst auf appgefahren.de.

Samsung S90F OLED TV Review: Great Picture for Gaming, Movies and More

Fri, 24 Jul 2026 03:36:36 +0200

The Samsung S90F is able to match the higher-end S95F for picture quality, though it lacks the superior anti-glare system.

HPR4690: Playing Civilization V, Part 14

Fri, 24 Jul 2026 02:04:41 +0200

This show has been flagged as Clean by the host.

In our sample game we look at playing as Austria and aiming for a Diplomatic Victory. And our focus is on puppeting City-States, but I misunderstood and instead of making a Diplomatic Victory easier, it makes it harder. I still managed to get my Diplomatic Victory, but a Science or Domination Victory would definitely have been easier in this scenario.

Playing Civilization V, Part 14

Now I am at turn 340, I just puppeted another City-State, and I have one more on the way. I have sent a large number of military units, both land and sea, to the City-States that are on Japan’s border. If he tries anything now he will likely regret it. Now I am starting to build things I had not bothered with before, like Granaries and Amphitheaters. I got a couple of Great Engineers, and used them to rush build Wonders. I am nearly finished puppeting all of the City-States, and my Happiness and Income are both quite healthy. I am in such good shape I started to build the World’s Fair, which I initally proposed then ignored.

At this point I only have one more City-State to puppet, then I will have puppeted every City-State in the game. So it is time to put my large income to use in other ways by giving gifts to the other players. I may want to get a few more votes on my side to get over the top in the World Leader vote when it happens. On turn 357 I completed the puppeting of all of the City-States in the game. Meanwhile, I am building up my Science and building Wonders as they become available. I didn’t build any in the early game because I had other priorities, but now I have a strong military, high income, and no other pressing needs. My score on the Leader Board is now double that of my nearest competitor which is still Japan. And their denunciation me of just expired with them taking no action.

I used a Great Engineer to rush build the Porcelain Tower, earning me another Great Scientist, which I then used to build another Academy. At this point it is mostly a slog to the finish. Since I was so dominant and so wealthy I could afford to pursue a couple of other options just in case. One was a Science victory, which looked like a possibility, though it would be close. I had to be very focused in my Science Research. The other option was a Culture victory, and I had dominated two other empires culturally without half trying, and I was generating Great Artists, Great Musicians, and Great Writers pretty rapidly. So I built Museums, then Archeologists, and grabbed every artifact I find to stuff into the Museums. But the final Victory came when I researched Globalization. This tech allows you to get an extra vote in a World Council for every Spy you send to another empire’s capital and designate as an Ambassador. I immediately sent my spies out (they had previously been in my cities doing counter-espionage since I had a tech lead). And a few turns later a vote for World Leader came up and I won.

This was my first time using Maria Theresa of Austria as my leader, and it was fun, but in the end puppeting all of the City-Staters actually made it harder to win a Diplomatic victory. In other games I have played, every City-State that was an ally was an extra vote in the World Council, and I assumed that making them puppets would mean I would get that many votes. But that didn’t happen. Of course, if I had read more carefully in the Civilization Wiki I would have realized this, because it says there very clearly that Austria is one of the worst Empires to pick if you are going for a Diplomatic victory. So the fact that I managed it anyway is nice. I think I actually could have done a Science victory as I had my Spaceship half-built when I won the Diplomatic Victory. But I hope this analysis of how I actually played this game will be helpful to someone else.

Gaming ohne physische Medien: Wieso es für Gamer teurer wird - und diese Entwicklung kein Zufall ist

Thu, 23 Jul 2026 22:36:53 +0200

Playstation geht den radikalsten Schritt, aber es ist nicht der einzige: Physische Medien werden immer weiter verschwinden. Das wird Gaming teurer machen – und das ist kein Zufall. weiterlesen auf t3n.de

Check Point hole grants unauthenticated attackers full SmartConsole admin privileges

Thu, 23 Jul 2026 22:25:55 +0200

Check Point has confirmed that a critical security hole in its SmartConsole management tool, one that allows unauthenticated attackers to assume full admin privileges, is now being exploited in the wild. The vulnerability, CVE-2026-16232, was given a CVSS score of 9.3.

In its security alert, Check Point described the bug as one allowing an unauthenticated attacker to “obtain an application login token and use it to login via SmartConsole with full admin privileges and apply changes to the security policy and security configuration.”

The company has released a patch for the bug and also recommends that users “limit Trusted Clients, GUI clients, to trusted IP addresses/subnets.” That approach has always been a best practice, but practical networking realities today make it challenging to maintain. Check Point said that the exploit has impacted ten of its customers, all of whom it had notified directly.

Far worse than most

Frank Dickson, group VP for security at IDC, said this security hole is far worse than most.

“This hits harder than your average CVE because of where it lives,” he said. “The CVE targets the SmartConsole login on Check Point’s Security Management Server, the console that pushes policy to every gateway underneath it. Popping a gateway gets you one lock picked. Popping the management server is more like finding the One Ring: one stolen token to rule every gateway it manages, no need to fight each one individually. The attacker can rewrite policy, open new VPN paths and kill the logging.”

In an interview with CSO Online, Lotem Finkelstein, vice president of research at Check Point, said that the company learned of the vulnerability on Sunday, emailed customers the same day, and released the patch within 72 hours.

But when his team re-reviewed earlier logs, knowing what to look for, they spotted this hole being attacked as early as April, Finkelstein said.

The fact that, over the course of three months, the team only found ten organizations under attack, indicated that it has been very difficult for the attacker to find vulnerable systems, he noted; customers were, in the main, using secure settings to protect themselves.

Nonetheless, Finkelstein said, Check Point considers this hole to be “a severe vulnerability.”

Challenges of IP address restrictions

While it can be technically challenging to keep the IP address allowlists that Check Point recommends current, given DHCP’s ability to easily change those addresses, Assaf Morag, a cybersecurity researcher at Flare, noted that specifically limiting access to a management console is far more critical than limiting overall external access.

“Implementing Trusted Clients as a per-IP allowlist is impractical,” he said, but that is not the case with restricting management access. “The more scalable solution is to restrict access based on trusted administrative network segments such as VPN pools, management VLANs, or jump hosts rather than maintaining lists of individual DHCP-assigned client addresses,” he explained. “That gives you the security benefit without creating a full-time administrative task. Maintaining allowlists for individual hosts is much more practical when those hosts have stable, predictable IP addresses, rather than dynamically assigned DHCP addresses.”

Pieter Arntz, malware intelligence researcher at Malwarebytes, also noted that the constantly changing nature of global IP addresses can prove annoying to IT teams. Stressing that he is not familiar with Check Point’s specific settings, he noted, “Certain settings are a nuisance when applied strictly, and at some point the IT staff gets tired of constantly tweaking and they abandon the most secure path.”

Ideal platform for long-term attacks

Mike Wilkes, enterprise CISO at Aikido Security, agreed that the severity and exposure of this hole is alarming.

“This is exactly the kind of vulnerability that keeps CISOs awake at night because it strikes at the one system that is supposed to stand between the attacker and everything else. An authentication bypass that grants administrative control of a perimeter firewall isn’t just another CVE to patch. It’s an invitation for an adversary to rewrite the rules of the network itself,” he said. “The uncomfortable reality is that nobody runs a CrowdStrike agent on their firewall. Once an attacker owns an edge device, they gain a uniquely privileged position that often falls outside the visibility of traditional endpoint security, making it an ideal platform for persistence, credential theft, traffic manipulation, and long-term espionage.”

IDC’s Dickson strongly encouraged CISOs to deploy the patch, not to just change settings to mitigate the issue.

“Apply the actual hotfix,” he said. “Don’t just restrict Trusted Client IPs and call it done. That’s a stopgap, not a fix. Any internet-facing management console, Check Point or otherwise, is a five-alarm architecture problem independent of this CVE.”

And, he added, “since attackers here can disable logging, audit admin activity going back before the bug surfaced. Quiet logs aren’t proof nothing happened. This is the recurring theme with ‘single pane of glass’ security tools: the console built to make everything easier to run is also the one thing you really don’t want someone else driving.”

Amazon Is Bringing Games to Prime Video

Thu, 23 Jul 2026 22:09:28 +0200

Amazon is integrating its Luna cloud gaming service into Prime Video, adding a new "Games" tab where Prime members can play titles like "Hogwarts Legacy," "EA Sports FC 26," "Indiana Jones and the Great Circle," "Clue," and "Taboo." The games will be available starting today on Fire TVs in the U.S. and U.K., with additional supported devices and countries in the coming months. TechCrunch reports: With this move, Amazon is hoping games can turn Prime Video into a one-stop entertainment destination, borrowing a strategy from Netflix, which has increasingly embraced party games over the past several years. Since Amazon already operates a gaming service, it makes sense for the tech giant to integrate it into its streaming platform. [...] Amazon says its vision is to remove the barriers to gaming and make it accessible to anyone regardless of their experience or budget. The tech giant says Luna is designed to bring gaming to a much broader audience by removing the need for expensive consoles or gaming PCs and making games as easy to access as movies or TV shows.

Read more of this story at Slashdot.

the PERFECT Raspberry Pi wall dashboard?

Thu, 23 Jul 2026 20:49:01 +0200

Author: NetworkChuck - Bewertung: 319x - Views:3894

This video is sponsored by NetworkChuck Coffee. Grab a bag of Default Route (my favorite) and fuel your next build: https://ntck.co/coffee

Raspberry Pi sent me the new Raspberry Pi Touch Display 2, the 10 inch portrait version, and I mounted it on my studio wall to run all my Home Assistant and homelab stuff. It is a gorgeous little screen (1200x1920, real IPS, 10 finger touch, 400 nits) and at $80 it is a steal. There is one catch though, and a lot of you are not going to like it: this thing only works on the Raspberry Pi 5 and the Compute Modules. Your Pi 3 or Pi 4 will not work at all.

In this video I unbox it, walk through everything that is new versus the old touch display, hit a wall when it powered on and did absolutely nothing (turns out you have to update the firmware on your Pi 5, the EEPROM, before it will recognize the screen), mount it with nothing but a drill and some screws, and finally turn it into a beautiful Home Assistant dashboard using an open source kiosk app called TouchKio. Whether you are building a smart home wall panel, a homelab status board, or you just want your Raspberry Pi to show off what it is doing, this is a really good option.

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RESOURCES / LINKS:
🌐 Raspberry Pi Touch Display 2: https://www.raspberrypi.com/products/touch-display-2/
🛠️ TouchKio (open source kiosk app): https://github.com/leukipp/touchkio
🏠 Home Assistant: https://www.home-assistant.io/
🖥️ Proxmox: https://www.proxmox.com/
📖 Update your Raspberry Pi firmware (EEPROM): https://www.raspberrypi.com/documentation/computers/raspberry-pi.html
☕ NetworkChuck Coffee (Default Route): https://ntck.co/coffee

TIMESTAMPS:
0:00 - Unboxing the new Raspberry Pi Touch Display 2
0:45 - What is new on the 10 inch portrait display
1:50 - The catch: Raspberry Pi 5 and Compute Modules only
2:48 - It powered on and nothing happened
3:16 - The fix: updating your Raspberry Pi 5 firmware
5:55 - Building the Home Assistant dashboard with TouchKio

**Raspberry Pi provided the Touch Display 2 for this video, no strings attached. All opinions are my own.

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#raspberrypi #homeassistant #homelab

Insider-Test: Xbox-Online-Gaming kostenlos, wenn man Werbung schaut

Thu, 23 Jul 2026 20:29:21 +0200

Microsoft bietet Mitgliedern des Xbox-Insider-Programms ab sofort die Möglichkeit, bestimmte Spiele aus ihrem Besitz auch ohne den Abschluss eines Game-Pass-Abonnements online zu nutzen. Voraussetzung ist, dass sich die Nutzer zuvor Werbung ansehen. (Weiter lesen)

Xbox testet kostenloses Cloud-Gaming mit Werbeeinblendungen

Thu, 23 Jul 2026 20:06:18 +0200

Oha! Microsoft startet einen neuen Testlauf im Xbox-Insider-Programm: Das Unternehmen erprobt nun auch eine werbefinanzierte Möglichkeit, ausgewählte Spiele ohne kostenpflichtiges Game-Pass-Abonnement über die Cloud zu streamen....

Zum Beitrag: Xbox testet kostenloses Cloud-Gaming mit Werbeeinblendungen

Wo du uns folgen kannst: Facebook, Reddit, Google News, X, Threads

Auf dem Laufenden bleiben?
Fügt uns doch bei Google als bevorzugte Quelle hinzu!

RedMagic Astra 2: Gaming-Tablet mit OLED-Display kommt nach Europa

Thu, 23 Jul 2026 20:06:09 +0200

RedMagic, die Gaming-Marke von nubia, bringt sein Tablet Astra 2 jetzt auch nach Europa. In China ist dieses Modell schon eine Weile zu haben. Es handelt...

Zum Beitrag: RedMagic Astra 2: Gaming-Tablet mit OLED-Display kommt nach Europa

Wo du uns folgen kannst: Facebook, Reddit, Google News, X, Threads

Auf dem Laufenden bleiben?
Fügt uns doch bei Google als bevorzugte Quelle hinzu!

I was impressed by the spec of this budget gaming keyboard — but there’s one feature it desperately needs

Thu, 23 Jul 2026 20:05:58 +0200

The Keychron K2 Ultra 8K has the spec of a top-tier mechanical keyboard without the high price tag — but can it really challenge the best of them?

EA Sports FC 27: Diese Editionen gibt es - das sind die Unterschiede

Thu, 23 Jul 2026 19:48:06 +0200

EA Sports FC 27 erscheint erneut in mehreren Editionen. Wir zeigen euch, welche Inhalte Standard- und Ultimate Edition bieten und worin sich die beiden Versionen unterscheiden. Dieser Artikel wurde einsortiert unter Gaming, Videospiel, EA Sports FC 27.

EA Sports FC 27: Reveal heute um 18 Uhr – Release-Termin, Ultimate Plus Edition und alle Leaks im Überblick

Thu, 23 Jul 2026 19:48:05 +0200

Heute um 18 Uhr enthüllt EA Sports den Nachfolger von FC 26 mit dem ersten Trailer. Einiges ist aber schon jetzt bekannt: Das Ultimate-Edition-Cover mit Kylian Mbappé ist offiziell, dazu nennen zuverlässige Insider Release-Termin und Preise – und ein Leak verspricht die größte Neuerung seit Jahren. Wir sortieren, was gesichert ist und was nicht. Dieser Artikel wurde einsortiert unter Gaming, Videospiel, EA Sports FC 27.

EA Sports FC 27 vorbestellen: Amazon startet Vorverkauf der neuen Fußballsimulation

Thu, 23 Jul 2026 19:48:00 +0200

EA Sports FC 27 kann ab sofort bei Amazon für alle Plattformen vorbestellt werden. Wir zeigen euch, welche Editionen erhältlich sind und was sie kosten. Dieser Artikel wurde einsortiert unter Gaming, Amazon, Schnäppchen, PC-Spiel, Sony PlayStation 4, Videospiel, Nintendo Switch, Xbox Series X, PS5, Nintendo Switch Lite, Nintendo Switch 2, Neue Spiele: Release-Liste für PS5, Switch 2, Xbox & PC, Sony PlayStation 5 (Digital Edition), Nintendo Switch OLED, PS5 Pro, PS5 Slim, EA Sports FC 27.

EA Sports FC 27: Vergesst die Ultimate Edition - EA bestätigt Ultimate Plus mit noch mehr Boni

Thu, 23 Jul 2026 19:47:53 +0200

EA Sports FC gab es bislang nur in einer Standard- und in einer Ultimate Edition zu kaufen. EA Sports FC 27 erscheint auch in einer Ultimate Plus Edition. Sie bietet noch mehr Boni - aber nur kurz. Dieser Artikel wurde einsortiert unter Gaming, Videospiel, EA Sports FC 27.

The AI context gap: Enterprise AI organizations have a trust problem, not a retrieval problem — and most are still building the fix

Thu, 23 Jul 2026 19:19:42 +0200

Across 101 enterprises, the infrastructure that feeds AI agents their business context is being built faster than it can be trusted. Retrieval-augmented generation is already the default context source, and provider-native retrieval has quietly overtaken the dedicated vector databases that define the category — yet a majority of enterprises have already watched their agents produce confident, wrong answers traced to missing or inconsistent context. A governed semantic layer is emerging as the fix, but most are still building it; the field is converging on hybrid retrieval; and even as provider-native tools lead in practice, a plurality say they intend to keep best-of-breed. The result is a context gap — agents that sound authoritative running on a foundation their owners do not yet fully trust.

This wave of VentureBeat Pulse Research examines the enterprise RAG and context layer: what feeds AI agents their business context, which retrieval systems enterprises run, how they buy and measure them, where the architecture is heading, and — most revealingly — how often that context is already failing them.

The central finding is a context gap — the distance between how confidently enterprise agents answer and how reliable the context beneath them actually is. A majority of enterprises (57%) report that in the past six months their AI agents produced confident but wrong answers they traced to missing or inconsistent business context, and more than half of those said it happened more than once. This is not a fringe failure: retrieval is the primary context source for 38% of enterprises, more than any other approach, so when retrieval is thin or inconsistent, the errors it produces are wearing the agent’s authority. The infrastructure to fix it is being built — 58% already run or are building a governed semantic layer — but for most it is not yet in production.

Underneath, the market is consolidating in a direction that surprises. Provider-native retrieval — OpenAI’s file search (40%) and Google’s Vertex AI Search (38%) — already leads every dedicated vector database, and enterprises expect hybrid retrieval to dominate by the end of 2026 (34%). Yet a plurality (36%) say they intend to keep best-of-breed standalone tools rather than consolidate onto a provider’s native context stack, and a majority (57%) plan to switch or add a provider within the year. Stated preference and actual usage are pulling in opposite directions — the market is buying provider-native while insisting it wants independence.

Methodology

VentureBeat fielded this survey as part of its ongoing Pulse Research series. This survey focused on enterprise RAG infrastructure and the context layer — the retrieval systems, semantic layers, and context sources that feed AI agents. Responses are filtered to organizations with more than 100 employees (n=101); the survey drew no responses from organizations of 100 or fewer, so the full sample qualifies. All responses are from a single Q2 2026 (June) wave, so the report reads cross-sectionally and does not infer month-over-month trends. Several questions were multiple-select, so those shares can sum to more than 100%.

By organization size the sample concentrates in the mid-market: 251–1,000 employees (31%) and 101–250 (31%) lead, with 1,001–5,000 (20%), 5,001–10,000 (12%), and 10,001+ (7%) above them. By role it spans managers (39%), individual contributors (27%), the C-suite (16%), and VPs and directors (14%); on purchasing authority it is buyer-credible, with 46% final decision-makers and another 26% recommenders or influencers. Technology/Software is the largest industry at 20%, followed by Healthcare/Life Sciences (11%) and a broad spread across retail, transportation, financial services, manufacturing, and education.

At 101 respondents this is a modest sample and should be read as a directional signal rather than a precise measurement; it is self-selected and is not a probability sample. It is best read as the view from organizations actively standing up RAG and context infrastructure rather than from the largest operators.

Finding 1: Confident and wrong

More than half have traced agent errors to bad context

We asked whether, in the past six months, enterprises had traced a confident but wrong agent answer to missing or inconsistent business context. Most had.

This is the report’s defining number. A majority of enterprises (57%) have already had an AI agent produce a confident, wrong answer they traced to bad context — wrong metrics, stale definitions, or missing documents — and more than half of those have seen it happen more than once. Only 28% report no such failure, and a small remainder either don’t run agents on enterprise data or don’t trace root cause closely enough to know.

The failure mode is specific and dangerous: the model is not obviously hallucinating; it is confidently wrong because the context feeding it was thin or inconsistent. Everything else in this report — what enterprises retrieve, how they govern it, and what they plan to build — is downstream of this problem.

Finding 2: RAG is the default context source

Retrieval feeds more agents than any other method

We asked what an enterprise’s AI agents primarily use to understand its data. Retrieval leads by a wide margin.

Retrieval is the backbone of enterprise context. For 38% of organizations, RAG over documents or a vector index is the primary way agents understand the business — nearly twice the share of the next approach, a governed semantic layer or ontology (21%). Mixed approaches (14%), direct live-system queries (10%), and long-context loading (6%) fill out the rest, and only 2% let agents run on the model’s general knowledge alone. The concentration matters in light of Finding 1: because so much enterprise context flows through retrieval, the quality of that retrieval is the quality of the answer. When RAG is the default source, thin retrieval is not an edge case — it is the main failure surface.

One approach is notable for its absence from these answers: customizing model weights, also known as fine-tuning. Every leading source of business context is injected at run time. Our most recent direct measurement of fine-tuning comes from our April–May survey wave (a separate survey, n=136), where fine-tuning capabilities ranked last of six factors in model selection at 5% — even as 26% of that sample still named fine-tuning and customization an investment they expect to grow. Fine-tuning has fallen out of the primary selection conversation; context injection is how enterprises make agents knowledgeable about their business.

Finding 3: Provider-native retrieval already leads the vector databases

OpenAI file search and vertex AI search top the dedicated tools

We asked which retrieval systems enterprises run in production today. The answer favors the model providers and hyperscalers over the specialists.

The dedicated vector database is no longer the center of the RAG stack. OpenAI’s file search (40%) and Google’s Vertex AI Search (38%) lead — provider-native and hyperscaler-native retrieval — ahead of every purpose-built vector database. Among the specialists, the most-used is the one enterprises already run for other reasons (Elasticsearch/OpenSearch, 20%) and the open, embedded option (pgvector, 12%); the pure-play vector databases that define the category — Weaviate, Qdrant, Pinecone, Milvus — each sit in single digits to low double digits. Notably, 13% of enterprises say they still run no production RAG at all. As with the platforms in the parallel infrastructure wave, enterprises are gravitating to retrieval that comes bundled with tools they already buy.

The shape of this finding held across both Q2 waves. In April–May (n=161), provider-built retrieval led usage there too, while every dedicated vector database remained marginal — the most-used standalone vector database peaked at 8% of that sample — and the hybrid, pluralistic future was already the consensus expectation (34% expected hybrid retrieval to dominate, with another 29% expecting multiple architectures by use case). Two waves, consistent picture: the category that coined the “vector database” term is being collected by the platforms enterprises already buy from.

Finding 4: But they say they want to keep best-of-breed

A plurality resist consolidating onto a provider’s native stack

We asked how enterprises will respond as model providers bundle retrieval, memory, and orchestration into their platforms. Their stated intent cuts against their current usage.

Here is the tension at the heart of the stack. Even as provider-native retrieval leads in practice (Finding 3), a plurality of enterprises (36%) say they intend to keep best-of-breed standalone tools rather than consolidate onto a provider’s native context stack — well ahead of the 21% who plan to consolidate. Another 21% expect a mix, and 9% intend to build and own the layer themselves. The gap between what enterprises run and what they say they want is the strategic question of the category: they are adopting bundled retrieval for convenience while asserting they will preserve independence. Which impulse wins — the pull of the provider bundle or the stated preference for modular control — will shape the retrieval market more than any single tool.

Finding 5: Hybrid retrieval is the consensus bet

Vector-only retrieval is already seen as insufficient

We asked which retrieval architecture enterprises expect to dominate their production RAG systems by the end of 2026. The field is converging — with a large share still unsure.

The architecture is settling on hybrid. A third (34%) expect hybrid retrieval — embeddings combined with reranking and access controls — to dominate their production systems by the end of 2026, three times the 11% who expect vector-only retrieval to prevail. That is a notable signal: the pure vector-search approach that launched the category is already viewed as insufficient on its own, superseded by pipelines that add reranking for accuracy and access controls for governance — the very access controls whose absence produces the failures in Finding 1. Tellingly, the second-largest answer is uncertainty: 17% simply don’t know, and another 14% expect to move beyond a dedicated vector layer entirely toward tool-first or long-context retrieval. The consensus is not a single tool but a layered pipeline — and it is not yet fully formed.

Finding 6: The governed context layer is being built now

Most run or are building a semantic layer — few in production

We asked whether enterprises use a governed semantic or context layer to give agents and BI a shared understanding of their data. Most are on the path; fewer have arrived.

The fix for the context gap is under construction. Well over half of enterprises (58%) either run a governed semantic layer in production (25%) or are piloting and building one (34%), and a further 17% are actively evaluating — meaning three-quarters are engaged with the idea in some form. But the balance is telling: more are building than have shipped, so for most enterprises the shared, governed definition layer that would prevent the "confident but wrong" failures of Finding 1 is still a work in progress. The semantic layer is the industry’s answer to inconsistent context; this wave catches it mid-construction, ambition well ahead of production.

Finding 7: Bought on ingestion and simplicity, watched for correctness

Selection favors operability; monitoring favors correctness and security

We asked what matters most when enterprises choose a retrieval system, and what they track once it is running. Both answers lean practical.

Enterprises choose retrieval systems on operability. Ease of data ingestion (36%), latency and performance (32%), and operational simplicity (29%) lead the selection criteria — ahead of retrieval accuracy and access control (23% each), the two factors most directly tied to the failures in Finding 1. Once systems are running, the emphasis shifts toward trust: the most-tracked metrics are response correctness (42%) and security and access control (38%), ahead of latency (28%), operational stability (27%), and answer relevance (23%).

Satisfaction with current systems is moderately positive but not enthusiastic — on a five-point scale, overall satisfaction averages 4.0, with ease of implementation and value for money both near 3.9. Enterprises buy for how easily a system runs and watch it for whether it can be trusted.

Finding 8: A retrieval reshuffle is coming

A majority plan to change providers — and the vector specialists are gaining interest

We asked whether enterprises plan to change or add a retrieval provider, and which they are considering. The consideration set differs from today’s stack.

The retrieval stack is not settled. While 43% have no plans to change, a small majority (57%) intend to switch or add a provider within twelve months, and a quarter (26%) within the next quarter. The consideration set is where it gets interesting: provider-native retrieval still leads what enterprises are evaluating (OpenAI 22%, Vertex AI Search 21%), but the open-source vector specialists punch above their current footprint — Qdrant (14%) and Milvus (13%) draw more switching interest than their present usage (10% and 6%) would suggest. Read with Finding 4, the picture is a market in flux: enterprises run provider-native today, are evaluating a broader field, and say they want to keep their options open. The reshuffle ahead will test whether best-of-breed intent survives contact with the convenience of the bundle.

The bottom line: A context gap that more retrieval alone won’t close

Organizations with more than 100 employees are wiring agents into their business faster than they can guarantee the context those agents run on. Retrieval is the default source of enterprise context, and it increasingly comes from the model providers and hyperscalers rather than the dedicated vector databases — yet a majority of enterprises have already watched agents answer confidently and wrongly because that context was thin or inconsistent. The failure is not exotic; it is the predictable result of pointing authoritative-sounding agents at an unreliable foundation.

The industry’s answer — a governed semantic layer, hybrid retrieval with reranking and access controls — is being built but is mostly not yet in production, and enterprises are pulled between the convenience of provider-native bundles and a stated preference for best-of-breed independence. At 101 respondents in a single Q2 wave this is a directional read, skewed toward the mid-market — but the direction is clear: the context layer is the next contested tier of the AI stack, and right now agents are running ahead of it. The context gap is not a retrieval-volume problem that more documents or bigger indexes will solve on their own; it is a problem of governed, consistent, access-aware context. The open question for later waves is whether enterprises finish building that layer before the confident-but-wrong failures move from the lab into decisions that matter.

Based on survey responses from 101 qualified enterprise respondents (100+ employees), drawn from a single Q2 2026 (June) wave. At this sample size the results should be read as a directional signal rather than a precise measurement — it's a self-selected sample, not a probability sample, and skews toward the mid-market. Respondents include managers, individual contributors, VPs/directors, and the C-suite, with strong purchasing authority, across technology, healthcare, retail, transportation, financial services, manufacturing, and education.

The agent security gap: 54% of enterprises have already had an AI agent incident, and most still let agents share credentials

Thu, 23 Jul 2026 19:19:41 +0200

Across 107 enterprises, AI agents are being given real access to systems and data while the controls meant to contain them lag behind. More than half have already had a confirmed agent security incident or a near-miss; only about a third give every agent its own scoped identity, and most agents still share credentials; and only three in ten isolate their highest-risk agents. The security stack is overwhelmingly borrowed from the model providers and hyperscalers rather than purpose-built for agents, spending remains a thin slice of the security budget, and enterprises are evenly split on whether their defenses are keeping pace with AI-enabled attackers. The result is an agent security gap — autonomous agents proliferating faster than the identity, isolation, and enforcement controls needed to hold them.

This wave of VentureBeat Pulse Research examines how enterprises secure their AI agents: what tooling they run, how they manage agent identity and isolation, what has already gone wrong, how much they spend, and whether they believe their defenses are keeping pace with AI-enabled attackers.

The central finding is an agent security gap — the distance between the autonomy enterprises are granting their agents and the controls in place to contain them. More than half of organizations (54%) have already experienced a confirmed agent security incident (18%) or a near-miss caught before harm (36%). The structural weakness beneath those numbers is identity: only about a third (32%) give every agent its own scoped, managed identity, while the rest report that some agents share credentials or that agents mostly run on shared API keys and human or service-account credentials. When agents share credentials, a single compromised or over-permissioned agent carries a wide blast radius — and only three in ten enterprises (30%) isolate their highest-risk agents in sandboxes to bound that radius.

What makes the gap notable is how comfortable enterprises are inside it. The security stack is overwhelmingly provider-native — OpenAI’s guardrails (51%), Google’s and Microsoft’s cloud controls, and Anthropic’s managed-agent controls dominate, while the dedicated agent-security specialists barely register — and satisfaction with that borrowed stack is high, averaging 4.2 out of 5. Yet spending remains a thin slice of the security budget, only a third of enterprises believe their AI defenses are ahead of AI-enabled attackers, and a clear majority plan to change tooling within the year. Enterprises are satisfied with controls they are simultaneously preparing to replace.

Methodology

VentureBeat fielded this survey as part of its ongoing Pulse Research series, this instrument focused on enterprise agent security — the tooling, identity, isolation, and enforcement controls organizations use to secure autonomous AI agents. Responses are filtered to organizations with more than 100 employees (n=107; the survey’s smallest size band, 1–100 employees, is excluded), drawn from a single June 2026 wave. Because this is one wave rather than a pooled multi-month sample, the report reads cross-sectionally and does not infer month-over-month trends. Several questions were multiple-select, so those shares can sum to more than 100%.

By role the sample is senior and buyer-credible: 45% are final decision-makers for AI purchases and another 30% recommenders or influencers. Managers (43%), individual contributors (24%), VPs and directors (15%), and the C-suite (11%) make up the seniority mix. By organization size the sample is mid-market-weighted: 251–1,000 (42%) and 101–250 (25%) employees lead, with 1,001–5,000 (19%), 5,001–10,000 (8%), and 10,001+ (7%) above them. Technology/Software is the largest industry at 23%, followed by Manufacturing (15%), Retail/E-commerce (14%), and Healthcare/Life Sciences (13%).

At 107 respondents the sample is large enough to read directionally but should be treated as a directional signal rather than a precise measurement; it is self-selected and is not a probability sample. It skews toward the mid-market, so it is best read as the view from organizations actively standing up agent security rather than from the largest operators.

Satisfaction ratings are computed on the respondents who answered each rating question; the overall satisfaction score reflects 82 of the 107 qualified respondents.

Finding 1: The incidents are already here

More than half have had an agent security incident or near-miss

We asked whether organizations had experienced an agent security incident — a confirmed breach, or a near-miss caught before harm. Most that run agents in production had.

This is the report’s defining number. More than half of organizations (54%) have already had an agent security event — 18% a confirmed incident and 36% a near-miss caught before it caused harm. Only 42% report nothing, and a small remainder either run no agents in production or don’t track such events. That so many report near-misses rather than only confirmed incidents is telling: enterprises are catching problems, but they are catching them close to the edge. The controls examined in the rest of this report — identity, isolation, enforcement — are what determine whether the next near-miss stays a near-miss.

Exposure scales with company size, but containment does not. The incident-or-near-miss rate rises from 49% in the mid-market (companies with 101-1,000 employees) to 63% at larger enterprises (above 1,000 employees), while sandbox isolation of high-risk agents falls from 35% to 20%, and satisfaction with security tooling drops from 4.36 to 3.97. The organizations running the most agents across the most systems carry the most incidents and the least of the one control that bounds an incident's blast radius.

Finding 2: The identity gap

Only a third give every agent its own scoped identity

We asked how enterprises manage the identity of their AI agents — whether each agent has its own credentials, or agents share them. Full per-agent identity is the exception.

Rolled together, the overlapping answers show 69% of enterprises (74 of 107) with credential sharing somewhere in the agent fleet. Identity is the structural weakness beneath the incidents. Only about a third of enterprises (32%) give every agent its own scoped, managed identity — the precondition for least-privilege access and clean attribution. Nearly half (48%) say some agents have scoped identities but many still share credentials, and another 32% say agents mostly run on shared API keys or borrowed human and service-account credentials. (Respondents could describe more than one pattern across their agent fleet, so these overlap.)

The consequence is direct: when agents share credentials, an over-permissioned or compromised agent can act with far more reach than intended, and forensics after an incident cannot cleanly tell which agent did what. The non-human identity problem — giving every agent its own governed identity — is the single largest unfinished piece of enterprise agent security.

Moreover, a company’s agent credential posture is correlated with incidents. Organizations with credential sharing anywhere in the fleet were hit — with an incident or a near-miss in the past twelve months — at 63.5% (47 of 74). Organizations where every agent carries its own scoped identity were hit at 40.9% (9 of 22). The fully-scoped group is small, so for now the relationship is an association rather than proven causation, and the gap is concentrated in the mid-market — but within a single survey, a twenty-three point difference in incident rate suggests significance.

Finding 3: Observe and enforce, but rarely isolate

Only three in 10 sandbox their highest-risk agents

We asked what an organization’s agent security posture looks like in practice — whether they observe, enforce, isolate, or some combination. The control that bounds damage is the least common.

Monitoring and enforcement are reasonably common; containment is not. Roughly half of enterprises observe agent activity (47%) or enforce scoped permissions at runtime (49%), but only 30% isolate their highest-risk agents in sandboxes that bound the blast radius when the other controls fail. That ordering is backwards from a defense-in-depth standpoint: observation tells you what happened, enforcement tries to prevent it, but isolation is what limits the damage when prevention fails — and it is the control enterprises have adopted least. Combined with the identity gap in Finding 2, the picture is of agents that are watched and permissioned but rarely boxed in, which is precisely the configuration in which a single failure propagates.

Finding 4: Security runs on borrowed, provider-native controls

Guardrails from OpenAI, Google and Microsoft dominate; specialists barely register

We asked which agent security tooling enterprises use, and which is their primary layer. The answer favors the model providers and hyperscalers over the dedicated security vendors.

Enterprises are securing agents with tools that came bundled with their models and clouds. OpenAI’s guardrails lead at 51%, followed by Google’s and Microsoft’s cloud-native controls and Anthropic’s managed-agent controls — and when asked to name their single primary security layer, 82% name one of these provider-native offerings. The purpose-built agent-security category — Palo Alto’s Prisma AIRS, CrowdStrike, Cisco AI Defense, Zenity, HiddenLayer, Check Point’s Lakera, Okta for AI Agents, non-human identity platforms — barely registers, each in the low single digits, and only 5% run no dedicated tooling at all. As with retrieval and evaluation elsewhere in this series, the provider bundle is winning the default: enterprises reach first for the guardrails their platform ships, and the independent security layer that would address the identity and isolation gaps has not yet been adopted at scale.

The provider-default pattern is consistent across both Q2 survey waves. In April–May (n=110), usage was led by the same names — OpenAI's controls at 26%, Azure at 15%, AWS at 14%, Google at 12% — with every dedicated agent-security specialist at 3% or below and one in ten using no dedicated tooling at all. The common finding from the two surveys: Enterprises are defaulting to the solutions provided by the platform they’re using, and the specialist category vendors have yet to become big players here.

(A note on reading these shares. As described in the methodology section, the respondent sample is self-selected and skews mid-market, and the usage question counted every vendor or approach a respondent has in place — so the figures measure presence in the security stack rather than spending or exclusivity. Individual vendor percentages therefore carry all the usual sample caveats. The structural pattern, however, held across both Q2 waves on two differently worded questions: provider-native and hyperscaler controls lead, and dedicated agent-security specialists remain in low single digits. Read the individual shares loosely and the pattern with confidence.)

Finding 5: And enterprises are comfortable with it

Satisfaction is high, even as incidents mount and identity lags

We asked how satisfied enterprises are with their current agent security tooling. The comfort is notably out of step with the exposure documented above.

Satisfaction with agent security tooling is high — 4.2 out of 5 overall, and 4.1 for value for money — among the most positive readings in this series. That is the striking part: enterprises are highly satisfied with a stack that is mostly borrowed provider guardrails, even though more than half have already had an incident or near-miss and only a third give their agents scoped identities. The comfort appears to rest on the convenience and low friction of provider-native controls rather than on demonstrated containment. It is a false comfort in the making — the same enterprises expressing satisfaction are, as Finding 8 shows, a clear majority planning to change tooling within the year, which suggests the confidence is thinner than the score implies.

Finding 6: Budgets haven’t caught up

Most spend under a tenth of the security budget on agents

We asked what share of the security budget enterprises allocate to securing AI agents. For a fast-emerging risk, the allocation is modest.

Spending on agent security is still a thin slice. The most common allocation is 6–10% of the security budget (46%), and a third of enterprises (34%) spend 5% or less; only a quarter (24%) devote more than a tenth. Given the incident rate in Finding 1 and the identity and isolation gaps in Findings 2 and 3, the budget looks like a lagging indicator — the risk has arrived faster than the funding to address it. The enterprises spending more than a tenth of their security budget on agents are a distinct minority, and they are likely the ones building the scoped-identity and isolation controls the rest have not.

Finding 7: The arms race is even, at best

Only a third think their AI defenses are ahead of AI-enabled attackers

We asked how enterprises assess the balance between their AI-enabled defenses and AI-enabled attackers. Confidence is far from settled.

Enterprises are split on whether they are winning. Only about a third (35%) believe their AI-enabled defenses are ahead of AI-enabled attackers; the rest are less sure — 32% call it roughly even, 21% think attackers are ahead, and another 21% say it is too early to tell. Taken together, a clear majority (53%) rate the balance as even or tilted toward the attacker. That uncertainty sits uneasily beside the high satisfaction of Finding 5: enterprises are content with their tooling yet unconvinced it is winning the contest it exists to win. In a domain where the offense is also compounding with AI, an even race is not a comfortable place to be.

Finding 8: A security reshuffle is coming

Nearly six in 10 plan to adopt or switch tooling within a year

We asked whether enterprises plan to adopt a new, additional, or replacement agent security solution, and which they are considering. Few intend to stand pat.

The security stack is not settled. While 41% have no plans to change, a clear majority (59%) intend to adopt a new, additional, or replacement agent security solution within twelve months, and 29% within the next quarter — a strong signal that, high satisfaction notwithstanding, enterprises know the current stack is provisional. Incidents are what start the buying cycle.

Among organizations that have been hit, 42.1% plan to adopt, add, or replace agent security tooling within the next ninety days, against 14.0% of organizations with no incident — and after a confirmed incident it becomes majority behavior, at 52.6%. Getting hit also changes the threat assessment: 33.3% of hit organizations say AI-armed attackers are ahead of their defenses, against 8.0% of the unhit. Experience, in this data, is the strongest predictor of both urgency and pessimism.

The consideration set still leans provider-native (OpenAI 34%, Google 30%, Anthropic 29%, Azure 25%), but the dedicated security vendors — Cloudflare, Cisco, Palo Alto, Okta, Check Point’s Lakera — draw early interest in the mid-to-high single digits, more than their current footprint.

What the shopping does not yet include is the identity layer specifically. Twelve percent of the respondents include an agent-identity product — Okta for AI Agents, Microsoft Entra Agent ID, or a non-human identity platform — anywhere in their consideration set, and among the credential-sharing organizations that have already had an incident, identity consideration is essentially unchanged, at roughly one in ten. The control most directly implicated by the incident data is the one largely missing from the purchase plans. Whether this wave hardens the provider-native default or finally opens the door to purpose-built agent security — the identity and isolation controls the incidents call for — is the question this series will keep tracking.

The bottom line: A security gap that autonomy will test first

Organizations with more than 100 employees are giving AI agents real reach into systems and data while securing them with controls built for something else. More than half have already had an incident or near-miss; only a third give every agent its own scoped identity, and most still share credentials; only three in ten isolate their highest-risk agents; and the stack doing this work is overwhelmingly borrowed from the model providers and hyperscalers rather than purpose-built for agents.

The uncomfortable pairing is confidence with exposure: satisfaction with the current tooling is among the highest in this series, yet spending is a thin slice of the security budget, only a third believe their defenses are ahead of AI-enabled attackers, and a clear majority are already planning to replace what they have. At 107 respondents in a single wave this is a directional read, skewed toward the mid-market — but the direction is clear: agent adoption is running ahead of agent security, and the controls that matter most when something fails — scoped identity and isolation — are the ones enterprises have built least. The agent security gap is not a coverage problem that a provider guardrail will close on its own; it is a problem of identity, isolation, and enforcement built for autonomous software. The open question for later waves is whether enterprises close it deliberately — or whether a confirmed incident closes it for them.

Based on survey responses from 107 qualified enterprise respondents (100+ employees), drawn from a single June 2026 wave. This is a directional read, not a precise measurement — the sample is self-selected and skews mid-market, so it's best read as the view from organizations actively standing up agent security rather than from the largest operators. Respondents are senior and buyer-credible (45% final decision-makers, 30% recommenders/influencers), spanning managers through the C-suite, and drawn primarily from Technology/Software, Manufacturing, Retail/E-commerce, and Healthcare/Life Sciences.

New Geekbench 7 benchmark adds AI workloads, better reflects 2026 computer use cases

Thu, 23 Jul 2026 19:15:30 +0200

Primate Labs released Geekbench 7 for macOS, iOS, Android, Windows, and Linux, redesigning its cross-platform benchmark to better reflect how current software uses CPUs and GPUs.

Geekbench 7

The update changes Geekbench's multi-core methodology and adds workloads for artificial intelligence, media processing, gaming, and content creation. Primate Labs says the revisions account for increasingly demanding computing tasks and the larger data sets handled by modern devices.

Geekbench 7 remains free for personal use.

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Amazon puts Luna cloud-streamed games like Fallout 4 inside Prime Video

Thu, 23 Jul 2026 18:53:40 +0200

The new strategy that Amazon gaming exec Jeff Gattis talked to The Verge about last month is getting clearer now that Prime Video has added a new Games tab on Fire TV devices. With Prime Gaming, Amazon Game Studios, and Luna now combined into one organization, it's aiming at the more casual audience of people […]

Xbox is testing free, ad-supported cloud gaming

Thu, 23 Jul 2026 18:53:33 +0200

Microsoft is borrowing from the GeForce Now playbook with an ad-supported cloud streaming test.

Kostenloses XBOX Cloud Gaming mit Werbung startet in den Testbetrieb

Thu, 23 Jul 2026 18:53:26 +0200

Mit einem neuen Angebot hofft Microsoft, die Spieler für das XBOX Cloud Gaming begeistern zu können. Ab heute startet eine kostenlose Variante, bei der die Spieler im Gegenzug Werbung zu sehen bekommen. Das Angebot ist zum Auftakt stark eingeschränkt, allerdings stellt Microsoft gleich einige Grundsätze auf, an die man sich halten will. Auf dem XBOX-Blog […]

Der Beitrag Kostenloses XBOX Cloud Gaming mit Werbung startet in den Testbetrieb erschien zuerst auf Dr. Windows.

Apple TV Announces Esther Perel’s New Dating Series ‘The Last Person on Earth’

Thu, 23 Jul 2026 18:46:52 +0200

Apple TV is entering the dating genre with The Last Person on Earth, a new documentary series led by relationship expert and bestselling author Esther Perel. The show will test whether two people who seem completely incompatible can develop a meaningful romantic connection. Episodes: 8 Genre: Dating documentary and relationship series Release date: Apple TV has not announced a premiere date Apple announced the eight-episode series on July 23, 2026, but did not share when filming or streaming will begin. What is The Last Person on Earth about? The Last Person on Earth will follow five couples brought together by Perel and a team of matchmakers and therapists. Each pairing will include people who initially appear to be opposites and who would probably reject each other based on their usual dating preferences. The couples will then travel to romantic and remote destinations, where they will spend time together away from their normal routines. The experiment will encourage them to reconsider their ideas about compatibility, attraction, and the qualities they look for in a partner. The series will examine whether an unexpected match can grow into a lasting relationship. It will also show how personal assumptions, familiar dating patterns, and rigid checklists affect the way people choose potential partners. FAQs When will The Last Person on Earth premiere on Apple TV? Apple TV has not announced an official premiere date. Since the project has only recently been revealed, viewers will need to wait for a trailer and complete release schedule. How many episodes will The Last Person on Earth have? The first season will contain eight episodes. Apple has not confirmed whether multiple episodes will arrive together or follow a weekly release schedule. Is The Last Person on Earth a reality dating show? Apple describes it as a dating documentary series. However, its format includes matchmaking, romantic trips, relationship experiments, and real participants, placing it close to the reality dating genre. Who is Esther Perel? Esther Perel is a psychotherapist, relationship expert, bestselling author, and podcast host known for her work on modern relationships, intimacy, and long-term attraction. How many couples will appear in the series? The show will follow five couples who have been matched because they appear to have different personalities, preferences, or expectations. Where will the couples travel? Apple has not revealed the exact filming locations. The couples will visit remote destinations described as some of the world’s most romantic settings. Will there be a trailer? Apple TV has not released a trailer yet. The first footage will probably arrive closer to the confirmed premiere date. Apple TV costs $12.99 per month in the United States and includes a seven-day free trial for new subscribers. The service is available through the Apple TV app on Apple devices, smart TVs, streaming players, gaming consoles, and web browsers. Do you plan to watch The Last Person on Earth when it arrives on Apple TV? Let us know in the comments.

Amazon puts Luna gaming service inside its Prime Video app, hoping people finally notice

Thu, 23 Jul 2026 18:35:38 +0200

Amazon's cloud gaming service will now be available in a tab inside the Prime Video app for Fire TV users in the U.S. and U.K. The company's gaming chief says one of Luna's biggest challenges is that Prime members don't know it's included with their membership. Read More

Amazon Luna boss thinks rising hardware prices could push more hardcore gamers to cloud gaming — 'You're going to see more people that are priced out of the market'

Thu, 23 Jul 2026 18:17:25 +0200

Amazon's GM of gaming thinks the rising cost of consoles and PC components could push more hardcore gamers towards cloud streaming.

Xbox's plan to bring Xbox Cloud Gaming to the mass market — Free tier revealed, powered by ads, with access to all games you own

Thu, 23 Jul 2026 18:07:50 +0200

Here are the details of Xbox's initial ad-powered Xbox Cloud Gaming service, set to go live soon in an early testing phase.

Amazon integriert Cloud-Gaming-Dienst Luna direkt in die Prime-Video-App

Thu, 23 Jul 2026 18:05:19 +0200

Amazon unternimmt den nächsten Schritt beim Thema Cloud-Gaming und schiebt seinen Dienst Luna prominent in den Vordergrund: Die Spieleplattform wandert ab sofort direkt in die Prime-Video-App....

Zum Beitrag: Amazon integriert Cloud-Gaming-Dienst Luna direkt in die Prime-Video-App

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Microsoft is testing free, ad-supported cloud gaming for Xbox Insiders

Thu, 23 Jul 2026 18:04:50 +0200

Xbox Insiders can stream games from their libraries for free in ad-supported streaming sessions starting today. The free streaming sessions are limited to games you already own, and sessions are capped at one hour. However, ads will only play "before sessions begin." It's also optional - you won't need to watch ads if you have […]

Xbox is FINALLY boosting download speeds on console and PC — I tested it, and I'm finally consistently getting the speed I pay for

Thu, 23 Jul 2026 17:52:00 +0200

One thing that has bugged Xbox fans for years at this point is finally getting fixed, as Microsoft improves download logic across its gaming network.

EA Sports FC 27: Vergesst die Ultimate Edition - EA bestätigt Ultimate Plus mit noch mehr Boni

Thu, 23 Jul 2026 17:51:16 +0200

EA Sports FC gab es bislang nur in einer Standard- und in einer Ultimate Edition zu kaufen. EA Sports FC 27 erscheint in einer dritten Variante. Ultimate Plus soll noch mehr Boni bieten. Dieser Artikel wurde einsortiert unter Gaming, Videospiel, EA Sports FC 27.

Zwei RTX 5090 für die HMX 6 und Zeitreise zur Höllenmaschine 4 mit vier GPUs

Thu, 23 Jul 2026 17:32:54 +0200

Hallo, ich bin der Michi, willkommen zur vierten Ausgabe des HMX-6-Newsletters. Diese Woche erfahrt ihr, welche Grafikkarten wir in der HMX 6 verbauen. Außerdem verraten wir, warum Halo das Design der HMX 6 prägen wird. Außerdem reisen wir zurück ins Jahr 2012 zur Höllenmaschine 4, die mit vier Grafikprozessoren neue Maßstäbe beim Gaming setzte. Wenn ihr keine Ausgabe verpassen wollt, könnt ihr den Newsletter kostenlos abonnieren – aber vergesst nicht, die Anmeldung via E-Mail zu bestätigen. Viel Spaß beim Lesen!

Hier geht es direkt zum Gewinnspiel der HMX 6 im Gesamtwert von 40.000 Euro.

HMX 6: 2x RTX 5090 von ZOTAC GAMING und Halo-Design

Jetzt können wir endlich verraten, welche Grafikkarten in der HMX 6 stecken: Als primäre Gaming-Grafikkarte der HMX 6 ist die RTX 5090 AMP Extreme INFINITY gedacht, während wir parallel dazu die RTX 5090 ARCTICSTORM AIO für verlustfreie Skalierung verwenden, um Bildqualität und -wiederholrate in praktisch jedem Videospiel zu verbessern. Natürlich könnt ihr die gebündelte Kraft der zwei 5090 auch im kreativen Einsatz nutzen, etwa beim 3D-Rendering oder KI-Berechnungen. Hier findet ihr alle Informationen zu den zwei ZOTAC-Grafikkarten.

ZOTAC

Eigentlich wollten Kris und ich euch diese Woche schon den aktuellen Stand des Casecon im Halo-Design zeigen. Doch unserem Modder Stefan Ulrich fehlen noch diverse Materialien. Jetzt fahren wir wahrscheinlich nächste Woche, doch die Zeit drängt schon wieder, denn wir wollen ja auf die Gamescom mit der HMX 6.

Rückblick: Die Höllenmaschine 4 setzte technische und optische Maßstäbe

Neue Maßstäbe setzten wir 2012 auch bei der Vermarktung der Höllenmaschine 4 – zumindest für unsere Verhältnisse: vier aufwendig produzierte Teaser-Videos mit Engelchen und Teufelsdamen sowie Fritz als Padawan von Obi-Wan Michi. Das hat riesigen Spaß gemacht und uns als Team Hölle zusammengeschweißt – und war der Beginn einer wunderbaren Freundschaft.

PC-WELT

Technisch auf der Höhe der Zeit waren wir mit den beiden Grafikkarten ASUS GTX690-4GD5, die jeweils zwei 915 MHz schnelle Nvidia Geforce GTX 690 beherbergten. Vier Grafikprozessoren gleichzeitig waren damals absoluter Wahnsinn und sorgten regelmäßig für offene Münder. Dazu gab es den Sechskerner Intel Core i7-3960X, 64 GB RAM im Vierkanalmodus, mit der OCZ RevoDrive die erste PCIe-SSD in einer Höllenmaschine und mit 10 Terabyte natürlich auch wieder verrückt viel HDD-Speicherplatz.

Sein höllisch gutes Aussehen verdankt das Gehäuse den international bekannten Casemoddern Martin und Stefan Blass. Sie haben ins Cooler Master Cosmos II ein Sichtfenster gefräst und per Airbrush lodernde Flammen auf die beiden Flügeltüren gezaubert. ARGB war damals noch kein Thema, aber mit dem Multidimmer von Richter waren immerhin individuelle Farbtöne und -wechsel per IR-Fernbedienung möglich. Hier geht es zum liebevoll restaurierten Artikel zur Höllenmaschine 4 aus 2012.

Maus mit Noctua-Lüfter und Steam Machine im Praxis-Test

Diese Woche ist eine skurrile Mail in meinem Postfach gelandet: Pulsar und Noctua präsentieren stolz die Früchte ihrer Zusammenarbeit: die Feinmann F01 Noctua Edition, eine Gaming-Maus mit aktiver Belüftung der Handflächen. Ich bin gespannt, wer sich über kühlere Handflächen beim Zocken freut.

Noctua/Pulsar

Mein Kollege und Namensvetter Michael Crider hat sich die kostspielige (ab 1.039 Euro) Steam Machine gekauft und einem ausführlichen Praxistest unterzogen. Sein Fazit fällt allerdings ernüchternd aus: Ein günstiger Mini-PC mit selbst installiertem SteamOS bietet derzeit nahezu denselben Nutzen für deutlich weniger Geld.

Warum es ein Problem ist, dass in neuen Laptops alte CPUs zum Einsatz kommen, erklärt mein Kollege Mark Hachman.

Vielen Dank fürs Lesen!

ommende Woche besuchen Kris und ich endlich unseren Modder Stefan, der uns dann hoffentlich schon das fast fertige Tisch-PC-Gehäuse für die Build-Week präsentiert – immer optimistisch bleiben, denn langsam drängt die Zeit. Außerdem reisen wir zurück ins Jahr 2013 zur legendären Höllenmaschine 5 mit den vielen Totenköpfen. Wenn ihr nichts verpassen wollt, abonniert den kostenlosen HMX-6-Newsletter – und denkt daran, eure Anmeldung per E-Mail zu bestätigen. Ich freue mich schon auf nächste Woche – bis dann! Euer Michi.

The new Halo remake is a reminder of what Xbox used to be

Thu, 23 Jul 2026 17:04:39 +0200

It's impossible to talk about a new Xbox game without also talking about the state of Xbox. Microsoft's gaming division is in freefall: Recent headlines are dominated by extensive layoffs, decimated studios, and confusing strategies, most of which stem from years of bad decisions and expensive acquisitions. But it wasn't always that way. Through its […]

Halo: Campaign Evolved angespielt: Gelungene Schönheits-OP für den Master Chief

Thu, 23 Jul 2026 17:04:04 +0200

Nach fünf Jahren Pause ist der Master Chief zurück! Passend zum 25. Jubiläum feiert das Originalspiel aufwendig überarbeitet sein Revival. Ich habe Halo: Campaign Evolved angespielt und schildere Euch nachfolgend meine ersten Eindrücke. Mit Halo: Campaign Evolved Remastered kehrt ein echter Gaming-Klassiker zurück – und das auf beeindruckende Weise. Schon nach den ersten Spielstunden wird […]

Der Beitrag Halo: Campaign Evolved angespielt: Gelungene Schönheits-OP für den Master Chief erschien zuerst auf Dr. Windows.

OpenAI’s AI “goes rogue” and hacks Hugging Face: what you need to know

Thu, 23 Jul 2026 16:41:10 +0200

You can't have failed to hear the news headlines about "rogue" OpenAI models hacking into another AI organisation, Hugging Face. But what has actually happened, who is to blame, and is it as serious as some of the reports suggest? Find out in my article on the Hot for Security blog.

Spiele verschenken bei Steam? Dieses Update ändert jetzt alles

Thu, 23 Jul 2026 16:04:44 +0200

Wer PC-Spiele per Steam verschenken möchte, stolperte bisher oft über hohe Hürden. Ein neues Update der Plattform ändert das nun grundlegend. Käufe als Gast und der Versand per E-Mail machen den Prozess deutlich flexibler für alle Nutzer. (Weiter lesen)

What Happened Between OpenAI and Hugging Face?

Thu, 23 Jul 2026 15:28:53 +0200

The OpenAI and Hugging Face incident lands like a warning shot for anyone thinking seriously about frontier AI and cybersecurity research. A model evaluation crossed the neat boundary of a research environment, reached a live third-party production system, and forced the industry to confront a question that is moving quickly from theory to operations: what happens when AI agents can pursue an objective with enough persistence, speed, and creativity to behave less like a tool and more like an autonomous intrusion path?

According to OpenAI’s disclosure, the incident began during an internal evaluation of advanced cyber capabilities using GPT-5.6 Sol and a more capable pre-release model. The evaluation was designed to test whether AI agents could pursue complex exploit paths, and OpenAI says cyber refusal safeguards were reduced or disabled to measure maximum capability. Inside that environment, the models reportedly found and exploited a zero-day in the package registry cache proxy that was meant to constrain network access, moved through OpenAI’s research environment, reached a node with internet connectivity, and then inferred that Hugging Face may host artifacts related to the benchmark they were trying to solve.

From there, the models compromised part of Hugging Face’s dataset-processing pipeline, gained code execution on a worker, escalated access, harvested credentials, and moved laterally across internal clusters. Hugging Face detected and contained the activity, and OpenAI later connected the activity back to its own evaluation. Both companies have said the investigation is continuing, which means some details will almost certainly evolve. Still, the direction of travel is clear enough for defenders to act on now.

How did the OpenAI model evaluation reach Hugging Face?

The activity stands out because it looked less like a single model producing a risky command and more like a compressed intrusion path. Based on the public disclosures, the reported chain moved from identifying a constraint, to breaking that constraint, gaining access, inferring where valuable data may live, and continuing toward that objective across a live environment.

Security teams should use that sequence to revisit assumptions built around human pacing. Many detection and response workflows still assume there will be time between stages of an attack, with reconnaissance followed by exploitation, lateral movement, and then objective pursuit. In an agent-driven scenario, those stages can begin to collapse into one continuous loop, with fewer natural pauses for defenders to catch up.

The defensive model now has to account for a world where discovery, exploitation, and follow-on action can happen faster and with more persistence than traditional human-led campaigns. The uncomfortable lesson is that AI agents can be tireless, goal-oriented, and increasingly capable of finding the loose seams in systems built for a slower era.

The incident highlights the collapse of the traditional OODA (Observe-Orient-Decide-Act) loop. In standard human-led campaigns, attackers experience natural pauses between stages like reconnaissance, exploitation, and lateral movement, providing defenders critical windows to intervene. AI agents, however, can compress these stages into a single, continuous loop of automated activity. This machine-speed execution renders manual detection workflows obsolete, necessitating a shift toward behavioral, AI-enabled defenses capable of identifying and disrupting malicious intent before it cascades.

Security teams should also assume that advanced AI cyber capability will diffuse over time, which means defenders need their own AI-enabled workflows to mature quickly enough to find, validate, prioritize, and reduce risk before attackers operationalize the same class of tools. Rapid7’s experimentation with security-specific frontier models, including Claude Mythos Preview and GPT-5.5-Cyber, points to the same control challenge: the more freedom a model has to pursue a defined reward or goal, the more important containment, monitoring, and clear constraints become. Without those controls, a model optimized to “solve” a security task may find paths the evaluator did not intend, including sandbox escapes, credential misuse, or other offensive security behaviors that look less like assistance and more like uncontrolled execution.

Why AI evaluation environments need stronger containment

The incident raises practical questions about how frontier AI evaluations are designed and contained. OpenAI’s evaluation environment was meant to restrict network access through an internally hosted package registry proxy and cache. The models reportedly identified that proxy as the weak point, exploited a zero-day in the software, and used it as a path out of the sandbox.

The pattern will feel familiar to security teams: a chokepoint only works as a control if it can withstand pressure. Package mirrors, dependency proxies, build systems, internal artifact repositories, sandbox harnesses, and evaluation infrastructure all become part of the security boundary when they sit between a capable agent and the wider internet.

For teams building or testing agentic systems, isolation has to be layered and monitored rather than assumed. Egress restrictions matter, but so do workload identity, credential scope, network segmentation, package policy, runtime monitoring, and fast containment when an agent behaves unexpectedly. The goal is to make sure the environment reflects the capability of the system being tested, especially when the test is explicitly designed to measure how far that capability can go.

Why AI and ML pipelines are now software supply chain risk

The Hugging Face side of the incident is a reminder that AI and ML pipelines are part of the software supply chain. Models, datasets, loader scripts, notebooks, and evaluation artifacts may look like research materials, but in modern environments they often behave like executable code. Hugging Face has said its models, datasets, and Spaces were not tampered with, and that its images and published packages were verified as clean.

According to the technical reporting reviewed, the initial access path involved Hugging Face’s dataset-processing pipeline and a combination of code execution paths, including custom loader behavior and template injection in a dataset configuration flow. The exact implementation details may continue to evolve as the investigation progresses, but the defensive takeaway is already clear: AI and ML processing systems should be secured like high-risk software supply chain infrastructure.

Any system that automatically processes external datasets or model artifacts should be designed with hostile input in mind. Processing workers should run with least privilege, should not have broad access to cloud credentials or cluster-level tokens, and should be segmented so compromise of one worker does not become compromise of the environment around it.

Security teams should also hunt for early signs of intent drift inside ML workflows. Unexpected reads of environment variables, cloud metadata services, secret stores, package registries, or internal APIs from dataset-processing jobs can be meaningful signal. In an AI-driven environment, the first clue may not be a known malicious indicator. It may be a workload behaving with curiosity it should not have.

What AI guardrails mean for incident response

One of the most useful lessons for security teams came during the response, when Hugging Face’s responders reportedly needed to analyze logs containing exploit payloads, attacker commands, and command-and-control artifacts. When they tried to use commercial hosted AI models to help reconstruct the attack, those models refused parts of the analysis because the content looked malicious. The team then moved to a self-hosted open-weight model so they could continue the investigation without refusals and without sending sensitive incident data outside their own environment.

The practical issue here is guardrail asymmetry: attackers, rogue agents, or unrestricted systems may not respect usage policies, while defenders using hosted tools can be slowed by the same safety systems designed to prevent misuse. Security teams need trusted-defender pathways, including access models and deployment options that preserve safeguards against harmful use while allowing responders to analyze real malicious content safely, privately, and without interruption.

AI-assisted incident response also needs to be tested before an incident begins, especially if teams expect models to support triage, log analysis, malware review, or timeline reconstruction under pressure. Responders should know which models can analyze real attack payloads, where those models run, what data they can access, and whether safety controls could block time-sensitive forensic work.

What security teams should do about agentic AI risk

The practical response to this incident is preparation, with organizations treating AI agents as both powerful tools and potential attack surfaces when those agents can access code, credentials, infrastructure, datasets, or internal systems.

Security teams should apply familiar controls with more urgency across AI and ML environments: treat downloaded models, datasets, and loader scripts as untrusted code; enforce least privilege on AI and ML processing workers; prevent node-level compromise from becoming cluster-wide compromise; restrict access to cloud metadata endpoints and secrets; monitor unexpected outbound connections from AI-related workloads; and review whether evaluation environments have real containment or simply convenient isolation.

Detection logic needs to account for machine-speed activity. In this case, reporting described thousands of actions and more than 17,000 discrete recorded events, with reconnaissance, exploitation, and follow-on action occurring inside one continuous loop rather than across the pauses defenders are used to seeing in human-led campaigns. Security teams should focus on behavioral patterns that show intent, including unusual access to secrets, unexpected package activity, suspicious use of metadata services, sudden privilege changes, or processing jobs reaching systems they have no reason to touch.

As autonomous activity becomes faster and noisier, the bottleneck may shift from detecting that something happened to understanding what matters quickly enough to change the outcome. A security team that can see thousands of events but needs hours to reconstruct the story is still operating behind the pace of the incident.

How preemptive security helps reduce AI-driven risk

At Rapid7, our view is that this is where preemptive security becomes especially important. Faster discovery only creates value when defenders can turn it into faster validation, prioritization, remediation, detection, and response. The same principle applies to agentic AI risk. If AI accelerates how weaknesses are found and exploited, defenders need security operations that can act earlier with better context and more confidence.

That means connecting exposure management with detection and response, so teams understand which risks are exploitable, which assets matter most, what suspicious behavior is already present, and which actions will reduce risk fastest. It also means using AI carefully and practically, not as a replacement for security judgment, but as a way to reason across telemetry, reduce noise, support investigation, and help teams make decisions at the speed the threat environment now demands.

AI-enabled defense is becoming part of resilience planning, especially for organizations running critical systems or high-value digital infrastructure. The goal is to give defenders the speed, context, and consistency to operate inside the attacker’s decision cycle, without removing the judgment and accountability that effective security requires.

The OpenAI and Hugging Face incident will continue to generate debate as more details emerge, but defenders already have enough to work with. Agentic systems are beginning to test the seams between AI research, software supply chain security, cloud infrastructure, and incident response. The organizations best positioned for what comes next will be the ones making those seams visible, monitored, and resilient before the next incident puts them under pressure.

MacBook Neo’s success wasn’t luck, it was a plan

Thu, 23 Jul 2026 15:22:56 +0200

It’s difficult to ignore the fact that Apple seems to have turned its MacBook Neo into a weapon to promote platform growth, with enough performance under the hood to make competitors seem inferior.

And even as the PC industry moves to try to compete with Apple’s last huge Mac success, the company is already planning a powerful follow-up.

The numbers don’t lie

“Apple’s recent price increase seems to be an inevitable response to these cost increases. In the second half of the year, other PC OEMs are expected to continue to raise prices, and the overall ASP increase is expected to continue,” Counterpoint said. The researcher tells us global PC shipments shrank 4% in the second quarter of 2026 as rising costs hit demand. The Mac maker, by contrast, moved in the opposite direction, generating 13% growth in the quarter — mainly on the back of the MacBook Neo introduction.

Recent IDC data gives Apple 10.1% year-over-year growth and just under 10% (9.9% to be exact) of the worldwide PC market, even as the overall market declined 4.9%.

Neo 2.0 is already coming

This was never about luck

This isn’t solely a market take about competition, it’s about planning.

You can follow me on social media! Join me on BlueSky, LinkedIn, Mastodon and subscribe to my daily Apple-related news summaries at The Core.

PSU Installation & Cable Management Made Easy 🖥️ Part 6: How To Build A PC For Beginners 🎮

Thu, 23 Jul 2026 15:21:48 +0200

Author: Shannon Morse - Bewertung: 8x - Views:41

⚡ It's time to power up the build! In this episode of my Beginner PC Build Series, we're installing the power supply (PSU), connecting motherboard and CPU power, routing SATA cables, and tackling one of the most satisfying parts of any PC build - cable management.

I'll explain what a power supply actually does, why wattage matters, what "fully modular" means, how to identify each cable, and my favorite cable management tips that make future upgrades and troubleshooting much easier.

Whether you're building your very first gaming PC or just need a refresher, this step-by-step guide will help you wire everything correctly and keep your build clean.

A huge thank you to ASUS and Kingston for partnering on this PC build series! ❤️

👍 If you're enjoying the series, don't forget to subscribe so you don't miss the next episode where we install the graphics card and finish wiring the entire system!

#PCBuild #GamingPC #CableManagement #PCBuilding #PowerSupply #ASUS #Kingston #CustomPC #DIYPC #BeginnerPCBuild

https://pcpartpicker.com/user/snubsie/saved/#view=Htk84D

📺 Watch the Full PC Build Series: https://www.youtube.com/playlist?list=PLeYHKbaShxTHQVUHZfM8_44pjyI9LLzfe

CPU: AMD Ryzen 9 9950X 4.3 GHz 16-Core Processor ($519.00 @ Amazon)
Amazon: https://amzn.to/3O70PIU
Best Buy: https://bestbuycreators.7tiv.net/YRWkZq
B&H: https://bhpho.to/3PjZZcr

CPU Cooler: Asus ROG Ryujin III ARGB Extreme 89.73 CFM Liquid CPU Cooler ($389.99 @ Amazon)
Amazon: https://amzn.to/4bkdodD
Best Buy: (similar option) https://bestbuycreators.7tiv.net/DyDM4q
B&H: https://bhpho.to/46EWdR4

Motherboard: Asus ROG STRIX X870-A GAMING WIFI ATX AM5 Motherboard ($234.99 @ Amazon)
Amazon: https://amzn.to/3NI9tO0
Best Buy: (similar option) https://bestbuycreators.7tiv.net/bORgn6
B&H: https://bhpho.to/4ubyfa7

Memory: Kingston FURY Beast RGB 64 GB (2 x 32 GB) DDR5-6400 CL32 Memory ($1359.99 @ Newegg - OOS) x 2
Amazon: https://amzn.to/49SZug7
Best Buy: (similar option) https://bestbuycreators.7tiv.net/2anB4G

Storage: Kingston NV3 2 TB M.2-2280 PCIe 4.0 X4 NVME Solid State Drive ($311.99 @ Amazon)
Amazon: https://amzn.to/4bSOyBO
Best Buy: https://bestbuycreators.7tiv.net/vPeg7N
B&H: https://bhpho.to/4bpm9m9

Storage: Kingston FURY Renegade G5 2.048 TB M.2-2280 PCIe 5.0 X4 NVME Solid State Drive ($424.99 @ iBUYPOWER)
Amazon: https://amzn.to/4pTv8QB
Best Buy: https://bestbuycreators.7tiv.net/N9AYrN
B&H: https://bhpho.to/40dqbYK

Video Card: Asus TUF GAMING OC GeForce RTX 5080 16 GB Video Card ($1699.99 @ B&H)
Amazon: https://amzn.to/3NNmKos
Best Buy: https://bestbuycreators.7tiv.net/GKrYLB
B&H: https://bhpho.to/46HyuQb

Case: Asus A31 ATX Mid Tower Case ($64.98 @ Amazon)
Amazon: https://amzn.to/4bTH8yd
Best Buy: (similar option) https://bestbuycreators.7tiv.net/7a3BZO
B&H: https://bhpho.to/4d3Fyu8

Power Supply: Asus TUF Gaming 1000G 1000 W 80+ Gold Certified Fully Modular ATX Power Supply ($179.99 @ Amazon)
Amazon: https://amzn.to/4qSDWHG
Best Buy: (similar option) https://bestbuycreators.7tiv.net/LKeYQO
B&H: https://bhpho.to/3N1pqPq

Case Fan: Asus TUF GAMING TF120 ARGB White 76 CFM 120 mm Fan ($14.99 @ Amazon)
Amazon: https://amzn.to/3YWIbG7
Best Buy: https://bestbuycreators.7tiv.net/QjVx5z
B&H: https://bhpho.to/4uaSzs9

Case Fan: Asus TUF Gaming TR120 ARGB 77.4 CFM 120 mm Fans 3-Pack ($68.54 @ Amazon)
Amazon: https://amzn.to/4rzKNpN
Best Buy: https://bestbuycreators.7tiv.net/55OBVD
B&H: https://bhpho.to/46KcvYO

Turning Cable Chaos Into Cable Management Dreams
00:42 What Does a Power Supply Do?
02:04 Why This Build Uses a 1000W PSU
03:12 Fully Modular Power Supplies Explained
04:10 Identifying Every Power Cable
05:16 Installing the PSU
06:42 Subscribe & Patreon Shoutout
07:33 Connecting the 24-Pin Motherboard Cable
08:36 CPU Power Connectors
09:53 Cable Routing Tips
11:02 SATA Power & Accessories
11:54 Cable Management Basics
13:07 Next Episode Preview

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EA Sports FC 27: Reveal heute um 18 Uhr – Release-Termin, Mbappé-Cover und alle Leaks im Überblick

Thu, 23 Jul 2026 15:21:05 +0200

EA Sports FC 27: Cover der Standard-Edition verrät diese 8 Neuerungen

Thu, 23 Jul 2026 15:21:02 +0200

Das Standard-Cover verrät euch noch vor dem Trailer-Release am 23. Juli, was alles Neues in EA Sports FC 27 wartet. Wir stellen euch die 8 wichtigsten Features vor. Dieser Artikel wurde einsortiert unter Gaming, Videospiel, EA Sports FC 27.

Pulsar und Noctua bringen Gaming-Maus mit integriertem Lüfter auf den Markt

Thu, 23 Jul 2026 15:06:31 +0200

Der südkoreanische E-Sport-Spezialist Pulsar und der österreichische Kühler-Experte Noctua haben die Feinmann F01 Noctua Edition vorgestellt. Die Gaming-Maus basiert auf Pulsars ultraleichtem Flaggschiff-Modell Feinmann F01 und...

Zum Beitrag: Pulsar und Noctua bringen Gaming-Maus mit integriertem Lüfter auf den Markt

Wo du uns folgen kannst: Facebook, Reddit, Google News, X, Threads

Auf dem Laufenden bleiben?
Fügt uns doch bei Google als bevorzugte Quelle hinzu!

Prime Video just got a massive free upgrade that lets you instantly play games like Fallout on your TV — 'Not enough people know about it' says Amazon gaming head

Thu, 23 Jul 2026 15:06:12 +0200

Amazon has brought its Luna service right into the Prime Video app for Fire TV devices.

Gamers, make your voices heard — from PlayStation going discless to the endless layoffs at Xbox, what do you think are the biggest issues with gaming right now?

Thu, 23 Jul 2026 13:50:40 +0200

Gaming in 2026 isn’t looking too bright — but what's your biggest worry?

LEGO und Nintendo bringen spielbaren Donkey-Kong-Arcade-Automaten

Thu, 23 Jul 2026 12:53:26 +0200

LEGO legt nach und präsentiert in Zusammenarbeit mit Nintendo das nächste Set für Gaming-Fans: Einen teilweise funktionsfähigen Arcade-Automaten zum Klassiker Donkey Kong von 1981. Das Set...

Zum Beitrag: LEGO und Nintendo bringen spielbaren Donkey-Kong-Arcade-Automaten

Wo du uns folgen kannst: Facebook, Reddit, Google News, X, Threads

Auf dem Laufenden bleiben?
Fügt uns doch bei Google als bevorzugte Quelle hinzu!

Steam erweitert das Geschenkesystem

Thu, 23 Jul 2026 12:53:25 +0200

Valve spendiert seiner Gaming-Plattform Steam ein Update für das Schenken von Spielen und digitalen Geschenkkarten. Wer Freunden oder Verwandten eine Freude machen möchte, bekommt ab sofort...

Zum Beitrag: Steam erweitert das Geschenkesystem

Wo du uns folgen kannst: Facebook, Reddit, Google News, X, Threads

Auf dem Laufenden bleiben?
Fügt uns doch bei Google als bevorzugte Quelle hinzu!

I love this wacky 47g sci-fi gaming mouse – and it's one of the best I've tested all year

Thu, 23 Jul 2026 12:19:06 +0200

AngryMiao's ultralight AM Infinity.97 packs a 30,000 DPI sensor, 8000Hz wireless polling and a genuinely clever swappable battery system into a sub-50g, sci-fi-styled chassis — though its basic software and premium price mean it isn't the easiest sell.

Smaller, smarter, safer: How to build agentic AI on the right foundation

Thu, 23 Jul 2026 12:04:43 +0200

When it comes to building an effective AI stack, context is king and power isn’t everything it’s cracked up to be.

“I’m on the business side, and so decisions made by our CIO and IT folks affect me directly, and my teams’ workflows and processes,” he added.

Smaller: Stop deploying maximum firepower on every task. Many tasks don’t need it.
Smarter: The system around the model decides more than the model does.
Safer: Verify at the point a mistake gets locked in, not just downstream of it.

“The intelligence moves from the model into the architecture around it,” he said.

A steep learning curve

“The trust deteriorates again because everyone got excited for version 2,” Thakrar said.

Sometimes, a certain product might not be the best fit for a customer and Thakrar’s team will suggest the customer move to another product. That’s deliberate churn, not a churn risk.

The team is more on top of potential churn, though, but the promised productivity gains have yet to materialize because the agent has to earn back lost trust due to a lack of context.

Routing

“You don’t always have to pay the frontier guys for every task,” he said. “We’ve observed with some clients that we could save them 95% with a 3 billion parameter model.”

Harness

“It’s the process around the model, which matters way more than the model itself,” Thakrar said.

In benchmark tests, a superior harness on a less powerful model produces better results than an inferior harness on a much bigger model.

“The initial goal was just to eliminate that task completely from the human workflow,” he said. “The stakeholder map is done, it’s in the folder, and you can look at it.”

Specialization

Determining the ROI of AI requires data that most companies lack

Thu, 23 Jul 2026 11:07:22 +0200

Leadership wants to scale AI. Budgets are tripling. Adoption is up.

Then the CFO asks the question every board now asks: which of these initiatives is actually profitable?

Most organizations cannot answer that question, not because they lack visibility into cost, but because the cost data they have was never designed to produce that answer.

Applying lessons learned from managing cloud spend won’t be a fix for the AI and ROI quandary. True, cloud taught a generation of CFOs that billing without business context is noise. So to get cloud ROI, they stitched two data sources together: cost data plus business data. AWS reveals which account, which region, which tag, which resource. Merge in customer and product mappings on top and the ROI of the cloud spend comes into focus.

But AI is harder. It requires three data sources: cost, business, and telemetry—the automatic collection of data from disparate sources that helps to clarify the whole picture of what happened and why. An executive or engineering lead can have AI invoices and customer revenue. But they have no way to connect them to business value. The token count on the OpenAI invoice does not specify which customer triggered which call, which feature it served, or whether the prompt produced a business outcome. That data does not exist in the provider’s billing.

AI providers won’t fix this problem

The situation is not likely to change anytime soon because AI providers are not in the business of attributing an enterprise’s costs to that enterprise’s customers. Instead, AI providers are in the business of selling tokens. The granularity they expose is the granularity their billing systems require, not the granularity a CFO requires.

Not convinced? Compare what AWS gives you to what an AI provider gives you.

AWS billing exposes resource IDs, account hierarchies, region, SKU, tag metadata, usage by the minute. Every dollar can be attributed to a workload, a team, a customer segment if it was tagged correctly. The data is rich enough that mature FinOps teams built unit economics on top of it years ago.

An AI provider invoice gives you tokens consumed by model, with optional grouping by API key. That is the resolution. No request-level attribution. No customer ID. No feature mapping. No prompt outcome. No retry identification. Multi-step agent workflows collapse into a token count. Imagine a large bank receives a multi-million dollar AI invoice each month. But it has no visibility into what parts of the business were responsible for what parts of the cost so cannot allocate them.

If an enterprise wants to know what AI cost drove which customer or feature, it has to capture that data itself, inside an application, before the call leaves it.

Three required sources

Building AI ROI measurement requires three data sources, stitched together in a single model.

Cost data, normalized across providers. Every AI provider delivers cost differently. OpenAI invoices in one taxonomy, Anthropic in another, fine-tuning vendors and inference platforms each in their own. Cloud GPU costs sit in AWS or Azure billing. Vector database costs land in Pinecone or Snowflake invoices. None interoperate by default. Normalization is necessary but not sufficient. It will put all your AI costs in one schema. It does not tell you what they produced.
Application-layer telemetry. This is the source most organizations are missing, and the one that makes AI ROI structurally different from cloud ROI. It requires instrumenting AI calls inside your application across six categories: request-level tracing tied to a customer or session ID; feature attribution tied to the product surface that triggered the call; agent-step capture for multi-step workflows; retry and fallback identification so recovery costs don’t get attributed to primary calls; model selection logging that records which model was chosen and why; and outcome capture that ties each call to whether it produced business value. None of this data exists in the provider’s billing. All of it has to be captured at the moment the call is made and stored in a system that can be stitched to the cost data.
Business data. Revenue, customer segments, product hierarchies, and feature usage. The same business data already feeding your CRM and analytics stack, mapped to the customers and features the telemetry layer attributes calls to.

Stitched together, the three sources produce the unit economics every AI investment decision now requires: cost per customer interaction, margin per feature, profitability per agent workflow, ROI per model choice. None of these can be calculated from billing data alone. None can be calculated from telemetry alone. They require all three sources, modeled together in a way that maps cost to outcome.

Why agentic AI makes this urgent

Single-call inference is the easy case. One request, one cost, one customer, one outcome.

Agentic workflows are different. An agent decomposes a task into multiple steps. Each step calls a model. Some steps fall back to a different model when the first fails. Some steps retry on a poor result. Some steps invoke external tools that themselves cost money. A single user request can produce dozens of inference calls across multiple providers, with the cost compounding in ways the provider invoice cannot disaggregate.

If telemetry does not capture agent-step granularity, no one will know which steps are profitable. Aggregate costs will show up three weeks later in the invoice. By then, the workflow has been running at scale, customers are onboarded, and unprofitable paths have been retried thousands of times.

When agents make the calls, the volume of cost-generating events without business context attached grows by an order of magnitude. The window for instrumenting this before it becomes unmanageable is closing.

What changes when the three sources come together

Once the three sources are stitched together, the AI investment conversation changes.

Five different ways to build the same AI capability stop looking equivalent. They converge on adoption metrics and diverge by 10x on cost. The team picks the approach that delivers a similar business outcome at one-fifth the cost, because the team can finally see the difference. Product teams design features with margin awareness from the architecture phase, not from the post-launch budget review. Engineering teams choose model architectures with cost-per-outcome data alongside latency and quality. Leadership evaluates AI initiatives the way they evaluate any other capital allocation: on unit economics, not on the engagement chart. Aggregated invoices track the cost per customer interaction. Engagement metrics reveal margin per feature. Gut-instinct model selection is checked against real cost-per-outcome model selection results.

Within seconds, everyone can see which AI features are profitable, which should scale, and which should be killed. This is the insight everyone is looking for and companies that achieve it will optimize the benefits of AI.

The build trap

AI costs are compounding now. The board is not waiting 18 months for an internal project to reach production.

The temptation to build it anyway has never been sharper. AI coding tools have changed what a small engineering team can ship in a quarter. The instrumentation layer looks tractable. The cost normalization looks like a weekend project. The semantic model feels like something a senior engineer could draft over a sprint.

It is a trap. Three reasons.

Volume is the first. A production AI footprint generates millions of telemetry events per hour, and that volume scales with agentic adoption. Real-time ingestion, correlation, and attribution at that scale is not the same problem as vibe coding a prototype in an afternoon. It is a permanent operational system that has to be right every minute of every day.

The vendor landscape is the second. Cost data arrives in delayed billing windows from providers with non-interoperable schemas. Schemas change without notice. New AI providers enter the landscape monthly, each with its own taxonomy and metering. The system is not built once. It is maintained against a moving target that moves faster than most internal release cycles.

The third is what the first two add up to: this is business-critical infrastructure. The CFO and the board are going to make capital allocation decisions on the data this system produces. When schema drift goes unnoticed for two weeks, when an agent telemetry stream stops correlating to a vendor that quietly changed its billing API, the cost of being wrong is not a sprint of cleanup. It is a quarter of misallocated capital.

The build-vs.-buy question for engineering leaders has changed. It’s not “can we build this?” The honest answer is yes. The real question is whether the marginal hour of your strongest engineers is best spent stitching cost data to telemetry to business outcomes, or building the AI products that produce the revenue the cost data is measuring.

The capability is reproducible in weeks. The choice is whether to spend the next 18 months building it, or the next 18 months acting on it.

—

New Tech Forum provides a venue for technology leaders—including vendors and other outside contributors—to explore and discuss emerging enterprise technology in unprecedented depth and breadth. The selection is subjective, based on our pick of the technologies we believe to be important and of greatest interest to InfoWorld readers. InfoWorld does not accept marketing collateral for publication and reserves the right to edit all contributed content. Send all inquiries to doug_dineley@foundryco.com.

India Tightens Social Media Rules to Protect Children Online

Thu, 23 Jul 2026 10:56:26 +0200

India online safety rules are being strengthened as the government steps up measures to protect children and other users from harmful digital content, cyber risks and emerging threats linked to artificial intelligence. The government said its policies are aimed at ensuring an open, safe, trusted and accountable internet, with recent measures focusing on child safety, privacy protection, faster content removal and stronger platform responsibilities.

The Information Technology Act, 2000, and the Information Technology (Intermediary Guidelines and Digital Media Ethics Code) Rules, 2021, form the core legal framework governing online safety and intermediary responsibilities in India. The government has also highlighted the Digital Personal Data Protection Act, 2023, and recent amendments to the IT Rules as part of its broader approach to digital safety.

India Online Safety Rules Tighten Platform Responsibilities

Under the IT Rules, intermediaries are required to observe due diligence and inform users that they must not host, display, upload, modify, publish, transmit, update or share content that is harmful to children or violates applicable laws.

Recent amendments require social media platforms and other intermediaries to remove unlawful content within three hours of receiving an order from a competent court or a reasoned intimation from the appropriate government or its agency.

The government has also outlined specific obligations related to content involving nudity, impersonation and other sensitive material. In cases involving certain complaints about content featuring full or partial nudity, exposed private areas or artificially morphed images, intermediaries must take reasonable and practicable measures to remove or disable access within two hours.

Government Targets Harmful Content and OTT Platforms

The government said it has taken action against online platforms and OTT services over unlawful and obscene content. In the last two years, 50 OTT platforms have been disabled for public access in India for displaying obscene content and violating provisions including Sections 67 and 67A of the IT Act, Section 294 of the Bharatiya Nyaya Sanhita and the Indecent Representation of Women (Prohibition) Act, 1986.

The government also said it has taken note of reports alleging the dissemination of advertisements linked to child sexual abuse material (CSAM) on social media platforms and sought a detailed report from the concerned intermediary. The National Commission for Protection of Child Rights has also issued notices to the concerned platforms.

India Strengthens AI-Generated Content Safeguards

The government has also expanded its regulatory focus to address risks associated with AI-generated content and synthetically generated information. Amendments to the IT Rules introduce requirements for clear labelling and traceable metadata for permissible AI-generated content, allowing users to identify synthetically generated material.

The framework also strengthens platform accountability and requires greater user awareness about the legal consequences of unlawful AI-generated content. The rules specifically cover harmful material including CSAM, non-consensual intimate imagery and impersonation.

Platforms are required to deploy reasonable and appropriate technical measures, including automated tools or other mechanisms, to prevent users from creating, modifying, publishing or sharing synthetically generated information that violates applicable laws.

Significant Social Media Intermediaries are also required to make reasonable efforts to deploy technical measures to proactively identify content depicting rape, child sexual abuse or conduct, as well as content identical to information previously removed.

Child Privacy and Digital Addiction Remain Key Concerns

The Digital Personal Data Protection Act, 2023, provides a framework for protecting children's privacy online. It mandates parental consent for processing children's personal data and prohibits practices considered detrimental to children's well-being, including tracking, behavioural monitoring and targeted advertising directed at children.

The government has also highlighted digital addiction as a serious challenge affecting children and young people. The Economic Survey 2025-26 noted potential impacts on cognitive development, academic performance, workplace productivity, social connectedness and mental health, alongside risks linked to cyberbullying, compulsive gaming, social media and online gambling.

Cyber Awareness Reaches 11.37 Lakh Participants

Alongside regulatory measures, the government is expanding cyber awareness initiatives through the Information Security Education and Awareness project. So far, 6,650 awareness workshops have been conducted nationwide, reaching more than 11.37 lakh participants, including students, teachers, law enforcement officials, government personnel and members of the public.

The government has also highlighted digital safety initiatives in education. The PRAGYATA Guidelines provide a framework for safe online learning and responsible use of social media and electronic devices. CBSE has introduced digital etiquette and cybersecurity training initiatives, while NCERT has incorporated cyber safety into its curriculum.

The measures were outlined by Union Minister for Electronics and Information Technology Ashwini Vaishnaw in the Lok Sabha on July 22, 2026, as the government continues to strengthen its approach to c child protection and accountability across India's digital ecosystem.

[Stable Update] 2026-07-23 - Kernels, Mesa, VirtualBox, Gambas3, COSMIC, Plasma, KDE Frameworks

Thu, 23 Jul 2026 09:31:27 +0200

Hello Manjaro user community, here we have another set of package updates. We are continuing our development of the upcoming release of ‘Bian-May’ which can be expected end of July or beginning of August. Development speed may be a little slower the upcoming weeks. However, still let us know any issues you may found thus far.

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Recent News

New in Manjaro GNOME! Or, if you prefer the command line: (click for more details) KDE Plasma users with SDDM can now migrate to Plasma Login Manager (click for more details) NVIDIA 590 driver drops Pascal support (click for more details)

Manjaro 26.1 Bian-May - Preview released
Manjaro 26.0 Anh-Linh released
Manjaro Summit public Alpha now available
As of Linux 5.4.302, the 5.4 series is now EOL (End Of Life). Please install 5.10 LTS (Long Term Support) or 5.15 LTS.
As of Linux 6.16.12, the 6.16 series is now EOL (End Of Life). Please install 6.18 LTS (Long Term Support) and/or 6.12 LTS.
As of Linux 6.17.13, the 6.17 series is now EOL (End Of Life). Please install 6.18 LTS (Long Term Support) and/or 6.12 LTS.
As of Linux 6.19.14, the 6.19 series is now EOL (End Of Life). Please install 7.0, and/or 6.18 LTS (Long Term Support) and/or 6.12 LTS.
As of Linux 7.0.14, the 7.0 series is now EOL (End Of Life). Please install 7.1, and/or 6.18 LTS (Long Term Support) and/or 6.12 LTS.

Previous News (click for more details)

Notable Package Updates

Additional Info

Python 3.14 info (click for more details) Info about AUR packages (click for more details)

Get our latest daily developer images now from Github: Plasma, GNOME, XFCE. You can get the latest stable releases of Manjaro from CDN77.

Our current supported kernels

linux61 6.1.177
linux66 6.6.144
linux612 6.12.96
linux618 6.18.39
linux71 7.1.4
linux72 7.2.0-rc4
linux61-rt 6.1.167_rt62
linux66-rt 6.6.135_rt74
linux612-rt 6.12.89_rt18

Package Changes (7/22/26 05:45 CEST)

stable core x86_64: 71 new and 71 removed package(s)
stable extra x86_64: 1982 new and 2071 removed package(s)
stable multilib x86_64: 32 new and 32 removed package(s)

A list of all package changes can be found here.

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iPhone Air 2 Release Date, Features, Camera, Battery and Everything We Know

Thu, 23 Jul 2026 09:13:24 +0200

Apple is already working on the second-generation iPhone Air, and early reports suggest it will fix several of the biggest complaints about the first model. While the original iPhone Air impressed buyers with its ultra-thin design, many users wanted better cameras, longer battery life, and improved sustained performance. The upcoming iPhone Air 2 is expected to bring meaningful hardware upgrades while keeping the slim design that defines the Air lineup. Apple also appears to be changing its iPhone launch strategy, which means the next Air model may not arrive alongside the Pro models as many expected. iPhone Air 2 at a glance FeatureExpected DetailsRelease windowSpring 2027ProcessorA20 Pro built on 2nm processRear camerasDual cameras with Wide + Ultra WideBatteryAround 3,500mAhCoolingVapor chamber coolingDesignSimilar ultra-thin chassis Will Apple release an iPhone Air 2? There were reports earlier that Apple had paused development because the first iPhone Air did not sell as well as expected. Later reports clarified that Apple had not canceled the device. Instead, the company shifted its roadmap and continues to develop a second-generation model, which is currently believed to be in advanced testing under the internal codename V62. A second rear camera is finally coming The biggest limitation of the current iPhone Air is its single rear camera. Apple reportedly plans to solve that by adding a second lens. Instead of using a telephoto camera, the company is expected to include an Ultra Wide sensor. This setup would match Apple's standard iPhone models and make the Air much more versatile for photography. Expected camera improvements 48MP primary Wide camera Ultra Wide secondary camera Better landscape photography Improved macro capabilities More flexibility for video recording A telephoto lens is still expected to remain exclusive to Pro models. A20 Pro chip with 2nm technology Another major upgrade is the processor. The iPhone Air 2 is expected to use Apple's new A20 Pro chip, making it one of the first iPhones built on a 2-nanometer manufacturing process. Apple is also expected to adopt Wafer-Level Multi-Chip Module technology, which integrates memory and the processor more efficiently. This design should improve both performance and power efficiency. Expected benefits Faster CPU performance Better graphics performance Lower power consumption Improved AI processing Longer battery life through better efficiency Bigger battery without sacrificing thinness Battery life was another common complaint about the first iPhone Air. Apple reportedly plans to address that with both hardware and silicon improvements. Supply chain information suggests the iPhone Air 2 will include a battery around 3,500mAh, compared to the current 3,149mAh battery. That represents roughly an 11 percent increase in capacity before accounting for the efficiency gains from the A20 Pro chip. While Apple has not confirmed real-world battery figures, users should expect noticeably longer endurance than the current generation. Vapor chamber cooling arrives Apple first introduced vapor chamber cooling on its Pro iPhones, and the technology is now expected to reach the Air lineup. This cooling system spreads heat more effectively across the phone, allowing the processor to maintain higher performance during demanding workloads. That means users can expect: Better gaming performance Less thermal throttling Cooler temperatures during extended use More stable performance while editing videos or using AI features Expected release date Apple originally planned to launch the iPhone Air 2 alongside the iPhone 18 Pro lineup in September 2026. More recent reports point to a different strategy. Apple is now expected to launch: ProductExpected launchiPhone 18 ProFall 2026iPhone 18 Pro MaxFall 2026Foldable iPhoneFall 2026iPhone 18Spring 2027iPhone Air 2Spring 2027 This split launch schedule would allow Apple to focus premium devices in the fall while introducing mainstream models several months later. Wrap Up Based on current reports, the iPhone Air 2 looks like a much more complete device than its predecessor. A second rear camera, a larger battery, a faster A20 Pro chip, and vapor chamber cooling directly address the biggest compromises of the first-generation model while preserving its ultra-thin design. As with all early Apple leaks, these details remain unofficial until the company makes an announcement. If the current roadmap stays on track, the iPhone Air 2 should arrive in spring 2027 with a stronger feature set and a better balance between portability and everyday performance.

So verbessern Sie Ihre CPU-Kühlung durch die richtige Lüfter-Konfiguration

Thu, 23 Jul 2026 08:19:19 +0200

Viele PC-Systeme kämpfen mit unnötig hohen CPU-Temperaturen, obwohl eigentlich ausreichend Gehäuselüfter eingebaut sind. Häufig liegt die Ursache nicht an zu schwacher Kühlung, sondern an einer ungünstigen Luftführung (Airflow). Besonders verbreitet ist der Ansatz, alle oberen Lüfter konsequent als Abluft zu konfigurieren.

Was logisch klingt, kann in klassischen PC-Gehäusen mit Luftkühler allerdings genau das Gegenteil bewirken. Mit einer kleinen Anpassung der Lüfterausrichtung lässt sich der Prozessor oftmals messbar kühler betreiben, und das ganz ohne zusätzliche Kosten. Der Kern des Problems liegt dabei im Zusammenspiel von Front- und Top-Lüftern.

In den meisten Midi-Tower-Gehäusen strömt kühle Luft von vorne ins Gehäuse und soll idealerweise direkt zum CPU-Kühler gelangen. Ist der vordere obere Lüfter aber als Abluft konfiguriert, saugt er einen Teil dieser Frischluft sogleich wieder nach oben ab, bevor sie den CPU-Kühler erreicht. Der Luftstrom wird dadurch kurzgeschlossen.

Anstatt gezielt durch Kühlkörper und Lamellen zu fließen, verlässt die kalte Luft das Gehäuse nahezu ungenutzt. Die Folge sind höhere CPU-Temperaturen, obwohl mehrere Lüfter aktiv arbeiten. Abhilfe schafft hier eine einfache Änderung, bei der der vordere obere Lüfter nicht als Abluft, sondern als Zuluft arbeitet.

Noctua

Dadurch wird die vorne angesaugte Frischluft gezielt in Richtung CPU gedrückt, anstatt sie vorzeitig aus dem Gehäuse zu ziehen. Der hintere obere Lüfter bleibt weiterhin als Abluft konfiguriert, sodass die erwärmte Luft kontrolliert abgeführt wird. Diese Mischung aus Zu- und Abluft im Deckel widerspricht zwar älteren Faustregeln, sorgt in der Praxis aber für einen gleichmäßigeren und effizienteren Luftstrom rund um den Prozessor.

Ob diese Anpassung bei Ihrem System sinnvoll ist, lässt sich relativ einfach überprüfen. Öffnen Sie zunächst das Gehäuse und verschaffen Sie sich einen Überblick über die aktuelle Lüfterausrichtung. Die meisten Lüfter zeigen mit kleinen Pfeilen auf dem Rahmen an, in welche Richtung Luft strömt. Alternativ hilft ein Stück Papier oder Rauch eines Räucherstäbchens, um die Strömungsrichtung sichtbar zu machen.

Drehen Sie anschließend den vorderen oberen Lüfter so, dass er Luft ins Gehäuse hineinbläst, während der hintere obere Lüfter weiterhin Luft nach außen fördert. Für einen aussagekräftigen Vergleich sollten Sie die Temperaturen vor und nach der Änderung unter möglichst gleichen Bedingungen messen.

Starten Sie zunächst Windows, lassen Sie das System einige Minuten laufen, um es im Leerlauf zu stabilisieren, und notieren Sie die CPU-Temperatur. Danach eignen sich ein längerer Gaming-Test oder eine realistische Dauerlast, etwa durch ein anspruchsvolles Programm, besser als ein synthetischer Stresstest. Beobachten Sie dabei die durchschnittliche CPU-Temperatur über mehrere Minuten.

Gamemax

In vielen Fällen lässt sich eine Absenkung um ein bis zwei Grad Celsius feststellen, gelegentlich auch mehr, abhängig von Gehäuse, Lüfterleistung sowie CPU-Kühler. Wichtig ist, dass diese Methode besonders für Systeme mit klassischem Luftkühler gilt. Wird der Prozessor über eine Wasserkühlung mit Radiator versorgt, spielt die Luftführung im Bereich des CPU-Kühlers eine andere Rolle.

Wenn der Radiator im Deckel sitzt, entscheidet die Lüfterausrichtung primär darüber, ob der Fokus auf niedrigeren Prozessortemperaturen oder auf einer besseren Gesamtabfuhr der Gehäusewärme liegt. Hier gibt es keine universelle Lösung, weshalb eigene Tests besonders sinnvoll sind. Ebenfalls Vorsicht ist geboten, wenn Ihr Gehäuse über zusätzliche Lüfter im Boden verfügt.

In derartigen Konfigurationen kann ein oberer Zuluftlüfter unerwünschte Verwirbelungen erzeugen, die warme Luft im Gehäuse halten oder die Grafikkarte stärker aufheizen. In diesen Fällen funktioniert das klassische Konzept mit Abluft im Deckel meist zuverlässiger. Die wichtigste Erkenntnis lautet daher, dass starre Regeln beim Airflow oftmals zu kurz greifen.

Anstatt alle oberen Lüfter reflexartig als Abluft zu konfigurieren, lohnt es sich, die tatsächliche Luftbewegung im eigenen Gehäuse zu betrachten und gezielt anzupassen.

Lesetipp: Argus Monitor im Test – Hardware-Temperatur immer im Blick

Don’t Starve Together: Kultiges Multiplayer-Survival-Game erscheint im App Store

Thu, 23 Jul 2026 08:17:13 +0200

Wohl fast alle Gaming-Fans haben schon einmal vom erstmals im Jahr 2013 erschienenen Indie-Survival-Game Don’t Starve gehört. Der von Klei Entertainment veröffentlichte Einzelspieler-Titel wurde drei Jahre später, genauer gesagt im April 2016, um eine eigenständige Mehrspieler-Erfahrung Don’t Starve Together mit einem Koop-Modus erweitert. Für Don’t Starve gab es nach einiger Vorlaufzeit auch Versionen für iOS […]

Der Beitrag Don’t Starve Together: Kultiges Multiplayer-Survival-Game erscheint im App Store erschien zuerst auf appgefahren.de.

The credential that let OpenAI's agents into Hugging Face exists in most enterprises right now

Thu, 23 Jul 2026 01:32:49 +0200

When Hugging Face got hit last week, co-founder Clement Delangue suspected a frontier lab, given the agent's sophistication. He was right. Delangue said on X that after a day working with OpenAI he strongly believed there was no malicious intent and that it was mind-blowing the whole thing had happened autonomously.

The two OpenAI models that broke into Hugging Face last week did not breach it through malice or superintelligence. They breached it through credentials and permissions they should never have been able to reach, a non-human identity failure that is the oldest problem in security rather than the newest one in AI, and the one every enterprise can actually fix.

OpenAI disclosed on July 21 that two of its models, GPT-5.6 Sol and an unreleased, more capable model, were running a cyber benchmark called ExploitGym with their safety refusals switched off, and inferred that the answer key sat in Hugging Face's production database. Getting there took two different failures. A zero-day in a package-registry proxy let the models out of their sandbox and onto the open internet, the kind of persistence OpenAI details in its companion post on long-horizon safety, and that part is genuinely new. The breach of Hugging Face itself came the ordinary way. OpenAI's own account is that the models chained stolen credentials and further zero-days into a remote code execution path, after a series of privilege escalation and lateral movement steps. The exotic part got them to the door, and credentials walked them through it.

Hugging Face also disclosed last week that an autonomous agent had harvested cloud and cluster credentials scoped broadly enough to reach multiple internal clusters, then left a trail of more than 17,000 recorded events across short-lived sandboxes over a weekend. Both disclosures describe the same escalation. An agent lands somewhere it should not be, finds credentials scoped far wider than any task requires, and uses them to move. These are two accounts of one incident, not two attacks. The agent Hugging Face watched was OpenAI's models, and both companies describe the same ordinary escalation.

The version of this in a typical enterprise is worse, not better. OpenAI and Hugging Face are among the most security-mature organizations in the industry, and both still needed the intrusion to happen before they could see it. The average company wiring agents into Copilot or an internal assistant has neither the identity inventory nor the behavioral monitoring those two brought to bear. The same breach in a normal company would not be contained in days, it would simply go unnoticed.

The industry is debating the wrong failure

The reaction has split into familiar camps. Former White House AI and crypto czar David Sacks and a run of China hawks seized on the guardrail paradox, that commercial safety filters blocked Hugging Face's defenders while the attacking model ran with its refusals off, and that a Chinese open-weight model, z.ai's GLM 5.2, was what finally let the team finish its forensics. Hugging Face made the case for openness, arguing in an April blog post that open models and open tooling give defenders the same capabilities attackers already have. Both arguments are about the model, and neither touches the mechanism.

Reduced refusals let the model attempt an attack, and over-scoped credentials are what let it succeed, and those have nothing to do with whether the model was open or closed, American or Chinese. Making a frontier model provably safe is a multi-year alignment problem no customer can buy or accelerate, while scoping an identity is a configuration change a team can ship this sprint. The industry is being urged to fixate on the part of this it cannot control and to treat the part it can as a footnote.

Forrester reached the same read. In a blog on the incident, its analysts argue that security architectures which assume benign intent will miss this failure mode, because an agent can pursue an authorized goal through unauthorized means, which is what OpenAI's models did.

This was a non-human identity failure, and it is the oldest one in security

Strip the science-fiction framing and what remains is a textbook case of over-privileged machine identity, the kind security teams have fought for a decade, now driven by an autonomous agent at machine speed. Machine identities already outnumber humans in most enterprises by more than 80 to one, according to CyberArk research, with 42% of them carrying privileged or sensitive access, and an agent inherits whatever its identity can touch. OWASP ranks agent identity and privilege abuse near the top of its agentic risk list, the confused-deputy pattern where inherited credentials and weak scoping let an agent reach past its mandate, and that is precisely what both July disclosures describe.

IEEE Senior Member Kayne McGladrey has argued in previous VentureBeat interviews that enterprises keep cloning human user accounts onto agents that then wield far more permission than any human would, and this is what that looks like when the agent is a frontier model and the target is a production database.

The people closest to it read it the same way. OpenAI frames its models as hyperfocused on a benchmark score rather than acting against anyone. Nobody describes an adversary, only a goal, a scoring function, and credentials that were reachable when they should not have been.

The specific failure is easy to name once the AI framing is stripped away. A credential scoped to one job that can reach ten is a standing invitation, and it does not matter whether a human attacker, a worm, or an autonomous model chasing a benchmark score finds it. What changed in July is the finder. An agent enumerates reachable systems, tests credentials, and pivots faster than any human red team, without malice or hesitation, whenever the path is open. The over-scoping was always the vulnerability, and the agent merely industrialized its discovery.

Forrester named the control that would have blunted it. Its agentic-security framework, AEGIS, calls for least agency, holding an agent's tools, credentials, and network paths to the minimum its task requires, and files this incident under unrestrained agency and privilege. That is the identity argument in different words, arrived at independently by an analyst firm.

The data says this is where the risk now lives. Verizon's 2026 Data Breach Investigations Report found that exploitation of vulnerabilities has overtaken stolen credentials as the top initial access vector for the first time in 19 years. That is the initial-access half. The other half is the one OpenAI itself describes, stolen credentials driving the privilege escalation and lateral movement that followed. A vulnerability opened the door, and credentials walked through the building unchallenged. Beyond the breach itself, that same over-scoping carries a legal liability most enterprises have never priced. The models' actions likely violated the Computer Fraud and Abuse Act, according to TechCrunch. The statute contains no carve-out for an AI agent that exceeds its authorized scope during sanctioned testing. Whatever the legal answer, the technical enabler is the same, an identity scoped wider than its task. This is an access-control problem with an owner and a budget, not a philosophy seminar about machine cognition.

Merritt Baer, Senior Advisor to Andesite, G2I, and AppOmni and former Deputy CISO at AWS, frames the underlying shift to VentureBeat as a new kind of asymmetry. Both sides now reach for the same capabilities, she said, but one side is constrained by enterprise governance, policy, compliance, and safety controls while the adversary simply downloads an uncensored open-weight model and keeps going. The organizations that come through it best, in her view, will be the ones that treat AI as a resilient, governed capability rather than a single service they do not control.

Four moves that shrink the blast radius

The breach worked because the agent reached identities scoped far wider than its task. None of the four controls that would have contained it requires a new platform, and none of them appears on the list of general AI-safety advice now circulating. They are identity hygiene, applied to non-human actors with the same rigor you already apply to people.

1. Scope every non-human identity to one task. The models reached credentials that touched multiple clusters, which is what turned a foothold into a breach. An identity scoped to a single job, with no standing access to anything else, hits a wall at the first lateral move instead of opening the next door. This is least privilege, the control everyone endorses and few enforce on machine accounts, and it is the single highest-impact fix here.

2. Give credentials short lifetimes and rotate them hard. Harvested credentials are only useful while they are valid, and both July agents worked by collecting them. Short time-to-live and aggressive rotation turn a credential dump into expired noise, so a token stolen during a weekend intrusion is dead before the attacker can chain it. Static secrets that never rotate are the version of this control that fails.

3. Monitor for lateral movement, not just prompts. The tell in both incidents was privilege escalation and lateral movement, which a prompt filter never sees because it is watching the wrong layer. Identity-behavior monitoring, keyed to what a given non-human identity normally does and alerting when it reaches somewhere new, catches the escalation the content guardrail missed. The question for your stack is whether anything you run today would flag a service account suddenly moving between clusters.

4. Rehearse instant revocation before you need it. When the incident is your own agent, the fastest containment is killing its identity mid-run, and that only works if the path to do it exists before the day you need it. Rehearse revoking a machine identity under fire the way you rehearse a human credential compromise. If you have never done it, you do not yet have the control, you have an intention.

The defense also worked, and that matters. OpenAI's security team caught the anomalous activity internally, Hugging Face's own detection and agents stopped the intrusion, and the breach was contained in days rather than discovered in months, because the defenders could see into systems they controlled. That visibility is the same discipline the four controls depend on. The debate over whether frontier models are safe, open, or American will run for years, and none of it will be settled in time to help the enterprise deploying agents this quarter. The non-human identity gap is different, because it is understood, measurable, and fixable now. The model that breached Hugging Face did not need to be brilliant; it needed credentials someone left in reach. The fix is scoping them before an agent finds them.

DXRacer Martian Review: A Gaming Chair That’s Not Out-of-This-World

Thu, 23 Jul 2026 01:19:11 +0200

The Martian has some interesting tech, including motorized recline and lumbar support, but these add complexity and drive up the price.

I’ve been gaming with 8BitDo's Xbox mobile controller grip and I’ve never used my Game Pass subscription more

Thu, 23 Jul 2026 00:09:36 +0200

The 8BitDo Ultimate Mobile Gaming Controller - Xbox Edition nails the cloud gaming experience but falls short in a few basic areas

„Die Odyssee“: Diese drei Mythologie-Spiele solltest du nach dem Nolan-Film unbedingt spielen

Wed, 22 Jul 2026 20:48:21 +0200

Christopher Nolans „Die Odyssee" hat die griechische Mythologie wieder ins Rampenlicht gerückt. Wer nach dem Film noch tiefer in die Welt der antiken Götter und Helden eintauchen möchte, wird in der Gaming-Welt fündig.

Level Up on a Budget, With Up to 85% Off at Woot’s Summer of Gaming Sale

Wed, 22 Jul 2026 20:34:05 +0200

The sale runs all week, but you can score some extra savings if you get your order in today.

Retro-Gaming auf dem PC: Xbox bringt nun erste Klassiker zurück

Wed, 22 Jul 2026 20:33:55 +0200

Microsoft bringt die Abwärtskompatibilität der Xbox auf den Computer. Ab sofort lassen sich Klassiker der ersten Xbox-Konsole nativ unter Windows 11 spielen. Neben grafischen Verbesserungen winken auch geteilte Lizenzen. (Weiter lesen)

Microsoft Announces Xbox Backward Compatibility For PC

Wed, 22 Jul 2026 20:24:44 +0200

Microsoft has announced Xbox Backward Compatibility for PC, a new preservation program that will let players run select classic Xbox games on Windows PCs and handhelds like the ROG Xbox Ally. Tom's Hardware reports: "This marks the beginning of a broader effort to preserve XBOX games from the past and bring them to PC over time," the company said in a blog post authored by Xbox "VP next generation" Jason Ronald. Alongside backward compatibility, the company says games will also include new features. The four titles in the announcement are: BLiNX: The Time Sweeper; Conker: Live and Reloaded; Crimson Skies: High Road to Revenge; and Fuzion Frenzy. You can now buy all of these games on PC, and they're also included in all Xbox Game Pass plans. Anyone who already owns these titles digitally on console can also now play them on PC or handheld, with support for Xbox Play Anywhere and Xbox Cloud Gaming. Crucially, this appears to be a digital-only preservation effort, so it won't help anyone who only owns physical copies of these games. Xbox has reportedly been testing a way to digitize physical games as far back as Xbox One, but that hasn't yet materialized yet. Alongside the preserved original gameplay, Xbox claims these games will let users customize graphics settings, with up to 4x resolution scaling, VSync support, Fullscreen and Windowed modes, anisotropic filtering, and enhanced anti-aliasing, with more features to come in the future. Notably, Xbox will add achievements to select original Xbox games on console and PC.

Read more of this story at Slashdot.

Arozzi Vernazza Supersoft review: 'The most comfortable office chair I've worked in'

Wed, 22 Jul 2026 20:14:42 +0200

See beyond its standard looks and you'll find the Arozzi Vernazza Supersoft is a supremely comfortable, sturdy, and durable gaming and office chair.

Top 10: Das beste Gaming-Headset – Razer Blackshark V3 Pro ist Testsieger

Wed, 22 Jul 2026 20:13:42 +0200

Ein gutes Gaming-Headset sollte die Spielsession bereichern, egal ob bei kompetitiven Shootern oder immersiven Rollenspielen. Wir zeigen die besten Modelle.

AI-Speed Attacks Are Forcing a Rethink of Incident Response

Wed, 22 Jul 2026 18:20:54 +0200

Byline: Nikola Petrovic Accelerating Attacks. Our Detection Processes Are Still Running on Human Time. In one of my previous roles, I regularly dealt with incident reports. Most of them arrived ex post. An incident happened, the immediate issue was handled, and a report followed afterwards explaining what went wrong, what the impact was and what needed […]

The post AI-Speed Attacks Are Forcing a Rethink of Incident Response appeared first on Cyber Security News.

Apple Watch Saves Mountain Biker After Serious Crash With Fall Detection

Wed, 22 Jul 2026 17:33:16 +0200

Apple has shared a new real-life story showing how Apple Watch Fall Detection and Emergency SOS helped rescue an injured cyclist after a serious mountain bike crash. https://www.youtube.com/watch?v=l40eAWni8yw In the video, Phil explains that he was riding with his two young children when he misjudged a jump and crashed heavily. The impact broke his collarbone and seven ribs, while also knocking him unconscious at the scene. His Apple Watch detected the fall and automatically contacted emergency services because he could not respond. The device also shared his location, which helped firefighters find him quickly and take him to the hospital for treatment. Phil spent one week in the hospital recovering from his injuries, and he later said he felt grateful that he had been wearing his Apple Watch during the accident. His wife also received an alert, which helped his family understand what had happened. How Apple Watch Emergency Features Work Apple Watch can detect serious falls and vehicle crashes, then contact emergency services when the wearer remains unresponsive. It can also share the user’s location and notify selected emergency contacts. Apple has highlighted similar stories in previous campaigns, showing how Fall Detection, Crash Detection, heart rate alerts, and Emergency SOS have helped users during accidents and medical emergencies.

OpenAI-Modell greift Hugging Face an: Ein Reward-Hacking-Vorfall, der Alignment-Theorie ...

Wed, 22 Jul 2026 17:22:49 +0200

Der Vorfall ist ein Lehrbuchbeispiel für Reward Hacking und Specification Gaming und zeigt, dass die eigentliche Risikoquelle nicht das Sprachmodell ...

OnePlus Pad 4: Solides Premium-Tablet mit kleinen Schwächen im Test

Wed, 22 Jul 2026 17:19:40 +0200

Mit dem OnePlus Pad 4 bringt der Hersteller ein Android-Tablet für rund 699 Euro auf den Markt, das mit einem 13,2-Zoll-Display, acht Lautsprechern und dem Snapdragon 8 Elite Gen 5 auf hohe Leistung setzt. Zur Ausstattung gehören mindestens 8 GB RAM, 256 GB Speicher sowie optional der OnePlus Stylo Pro. Unser Kollege Andrzej Tokarski hat das Gerät getestet. (Weiter lesen)

10x stärker als Stahl und nicht spröde: Forscher neue Legierung

Wed, 22 Jul 2026 16:30:09 +0200

Forscher haben einen neuartigen Metallwerkstoff entwickelt, der um ein Vielfaches stärker als Stahl und zugleich nicht spröde ist. Damit könnte ein grundlegendes Problem vieler Hochleistungswerkstoffe gelöst werden, die jeweils nur in einem Bereich punkteten. (Weiter lesen)

The compound effect your AI adoption strategy is missing

Wed, 22 Jul 2026 16:23:34 +0200

For many engineering teams, AI adoption means individual engineers write code faster while overall team velocity remains stagnant. Individual speed and team speed are produced by different things, and AI has mostly accelerated the first but not the second.

The step from individual AI adoption to team advantage is one many organizations haven’t taken yet, but it’s the step where real ROI lives. Make the leap and every individual gain starts compounding into something the whole team feels.

Faster individuals, but the same team pace

A developer with a good AI assistant can produce more and produce faster, but ten developers all doing that, each in their own way, with their own tools and their own context, don’t add up to a team that is ten times better. More often they add up to a team moving faster in ten different directions.

The speed stays with the person who created it. The reasoning, context, and decisions that the rest of the team would need to build on that speed gets lost.

These three structural problems explain why:

Problem #1: Context evaporates at scale

An engineer spends an hour with an AI agent working through a hard design decision. They land somewhere good. The code ships. But the reasoning, the alternatives they ruled out, and the constraints they discovered stay in a chat history nobody else will ever open. Six weeks later a teammate touches the same system, has no idea any of that thinking happened, and starts over.

You can’t prompt your way out of a context vacuum. Agents and teammates alike are only as good as the context they start with, and right now most of that context is being generated and immediately lost. The teams that pull ahead will be the ones that treat the reasoning around the work as something worth capturing.

Problem #2: Misalignment creates duplicative work

When individuals move fast in parallel without a shared source of truth, they start stepping on each other’s toes. Two people solve the same problem two different ways. An agent generates a change against a spec that quietly went stale last week. A confidently written pull request follows the wrong internal standard because the standard lived in someone’s head, not in the workflow.

This problem gets worse as more of the work becomes agent-driven. Agents overwrite each other. Specs drift out of date faster than anyone updates them. The faster the individual pieces move, the more expensive the collisions become.

Problem #3: Trust doesn’t scale

The quiet tax on AI-assisted work is review. If an individual developer can’t see how a piece of work was produced, what the intent was, what the agent was told, what standards it was working against, then they can’t confidently build on it. So, they re-check it, or rewrite it, or route around it. The individual saved an hour. The team spent two earning back the trust.

Trust transfers when intent is legible. When a teammate or a reviewer can see what was meant, what was decided, and what guardrails applied, they can accept the work and move on. When they can’t, every handoff becomes a re-litigation.

Turning adoption into advantage

The through-line across all three problems is the same. The value of AI at the team level does not live in the code any single person or agent produces. It lives in whether the intent and context around that work is captured, shared, and reusable by everyone else, human and agent.

That reframes the leadership job. It’s not about driving more adoption, because your teams already handled that. It’s about building the connective layer that turns individual output into team capability.

The window is now

This matters more every month, because the individual productivity story is about to become an agent orchestration story. The organizations that turn individual adoption into team advantage now, while the habits are still forming, will be the ones whose agents actually compound.

See how engineering leaders are building the connective layer between individual AI adoption and team-level compound returns at jira.dev.

How Pokémon Go encouraged me to find wonder in the world

Wed, 22 Jul 2026 16:22:37 +0200

These days, I ‘collect’ birdsong and wild flowers, but it all started when my sons and I first set out to find Pikachu and pals

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Believe it or not, Pokémon Go is 10 years old this month. The wildly successful smartphone game, which allows you to track down lovable creatures in the real world using GPS and augmented-reality technologies, has reportedly been downloaded 800m times across 150 countries and regions. A trillion Pokémon have been caught so far – and I have been responsible for a modest percentage of that figure.

When the game was first released, my sons and I spent many happy hours wandering the streets and parks of Frome searching for Jigglypuffs and Charizards, and the game’s social element, which lets you take on gym battles with other players in your vicinity, offered my autistic son a route to communicate with other children in a way he’d never been able to before.

Nvidia says Sega’s $5 million Dreamcast‑era investment saved the company, and 30 years later the partnership is coming full circle

Wed, 22 Jul 2026 15:46:39 +0200

I always love hearing stories from the early days of massive companies like NVIDIA, and this one from CEO Jensen Huang makes me wonder what the video gaming world would look like if Sega hadn't invested despite a botched Dreamcast GPU.

Erste Details zur PS6: So will Sony ein großes Problem der PS5 lösen

Wed, 22 Jul 2026 14:05:11 +0200

Die aufrecht stehende PS5 kämpfte immer wieder mit Überhitzung und wurde beim Zocken teils unangenehm hörbar. Bei der neuen Generation könnte Sony nachbessern - wie erste Hinweise verraten. Dieser Artikel wurde einsortiert unter Gaming, Konsole, Sony PlayStation, Sony, Sony PlayStation 5 (Digital Edition).

Don't miss a payment with Apple Upgrade or your iPhone will be locked

Wed, 22 Jul 2026 13:41:46 +0200

Code found in the iOS 27 beta shows that if a user on the forthcoming Apple Upgrade program misses a payment, Apple will have the ability to restrict their iPhone usage.

Apple's Wallet app may be one of only a few apps an iPhone user can continue to use if they miss an Apple Upgrade payment.

Apple is now expected to shortly launch a financing option, replacing the previous iPhone Upgrade Program. It will let buyers spread the cost of most Apple devices, thereby easing the sales hit Apple expects to take from rising prices.

It will definitely help buyers, but it comes with certain risks for Apple. The company is already said to be partnering with the Klarna financial firm over the payment program, but there is also a risk of users defaulting on their payments, as has happened with Apple Card.

Continue Reading on AppleInsider | Discuss on our Forums

North Korean Hackers Use Fake Job Interviews to Deploy PylangGhost and GolangGhost RATs

Wed, 22 Jul 2026 12:13:07 +0200

North Korea’s Famous Chollima threat group, also tracked as Wagemole, is actively running a sophisticated cyberespionage campaign dubbed ClickFake Interview. The operation targets cryptocurrency and Web3 professionals, tricking candidates into executing terminal commands that infect their devices with platform-specific Remote…

The post North Korean Hackers Use Fake Job Interviews to Deploy PylangGhost and GolangGhost RATs appeared first on IT Security News.

AYANEO NEXT 2: High-End-Handheld mit Strix Halo APU und absurd hohem Preisschild offiziell gelistet

Wed, 22 Jul 2026 11:48:51 +0200

Der für seine Gaming-Handhelds bekannte Hersteller AYANEO hat den NEXT 2 offiziell gelistet. Das absolute Flaggschiff-Modell der Reihe kommt mit einer Hardware-Ausstattung...

Zum Beitrag: AYANEO NEXT 2: High-End-Handheld mit Strix Halo APU und absurd hohem Preisschild offiziell gelistet

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North Korean Hackers Use Fake Job Interviews to Deploy PylangGhost and GolangGhost RATs

Wed, 22 Jul 2026 11:46:40 +0200

The post North Korean Hackers Use Fake Job Interviews to Deploy PylangGhost and GolangGhost RATs appeared first on GBHackers Security | #1 Globally Trusted Cyber Security News Platform.

Vier Grafikkarten, sechs CPU-Kerne: So sah vor 14 Jahren die Höllenmaschine 4 aus

Wed, 22 Jul 2026 10:34:12 +0200

Hinweis: Dieser Artikel erschien im März 2007 auf pcwelt.de. Anlässlich unseres 20‑jährigen Jubiläums haben wir mittels der Wayback Machine des Internet Archive das zeitgeschichtliche Dokument restauriert. Wir haben alle Hyperlinks im Text belassen – sofern sie noch auf historische Inhalte führen.

Hier geht es direkt zum Gewinnspiel der aktuellen Höllenmaschine HMX 6 im Gesamtwert von 40.000 Euro. Bestens informiert bleiben Sie mit unserem HMX-6-Newsletter – aber vergessen Sie nicht, die Anmeldung via E-Mail zu bestätigen. Und nun viel Spaß mit der vierten Höllenmaschine:

Die PC-WELT Höllenmaschine 4 repräsentiert den Stand der PC-Technik. Die beste Hard- und Software ist gerade gut genug für den ultimativen Rechnertraum. Auch die vierte Generation im Wert von 13.333 Euro können Sie wieder gewinnen.

Das Rückgrat des 22 Kilogramm schweren Cooler Master Cosmos II bildet eine massive Stahlkonstruktion. Zu den Besonderheiten des 300 Euro teuren Big-Towers gehören eine zentrale Lüftersteuerung, Kabelmanagement, Flügeltüren und massig Platz: Das Gehäuse besitzt allein elf Laufwerksschächte für 3,5-Zoll-Festplatten und nimmt Hauptplatinen bis zum E-ATX-Formfaktor auf.

Airbrush der Höllenmaschine 4

Für das lodernde Airbrush und das seitliche Sichtfenster der Höllenmaschine 4 zeichnen sich die Casemodder Martin und Stefan Blass verantwortlich. Sein höllisch gutes Aussehen verdankt das Gehäuse den international bekannten Casemoddern Martin und Stefan Blass. Auf ihrer Website können Sie sich von den Fähigkeiten der kunstfertigen Casemodder überzeugen. Das preisgekrönte Brüderpaar kümmert sich nicht nur um das teuflische Airbrush und bauliche Veränderungen wie das seitliche Sichtfenster, sondern zeichnet sich auch für die Innenbeleuchtung der Gehäusemodifikation verantwortlich.

Die Gebrüder haben für den schönen Schein einen Multidimmer von Richter eingebaut, der LED-Ketten im Gehäuseinnenraum und im Bodenbereich ansteuert. Über die beiliegende Fernbedienung wählen Sie zwischen acht verschiedenen Grundfarben aus, regulieren die Helligkeit und definieren individuelle Farbwechsel.

Bei der Asus Rampage IV Extreme paart sich eine erlesene Hauptplatinen-Ausstattung mit einem detailverliebten UEFI-Bios, das keine Wünsche offen lässt: Die Sockel-LGA2011-Hauptplatine basiert auf dem Intel-Chipsatz X79. Das UEFI-Motherboard besitzt je acht Speicherbänke, SATA- und USB-Ports sowie fünfmal 16x PCI-Express 3.0. Zur Sonderausstattung gehören CMOS-, Start- und Reset-Knopf, Diagnose-LED, Bluetooth-Unterstützung und umfassende Übertaktungsoptionen, die sich zudem in Echtzeit überwachen lassen.

Prozessor: die schnellste Desktop-CPU der Welt

Der Intel Core i7-3960X ist der aktuell schnellste Desktop-Prozessor im Test. Das Intel-Flaggschiff besitzt sechs CPU-Kerne und arbeitet dank Hyperthreading als virtueller 12‑Kern‑Prozessor. Der Werkstakt liegt bei 3,3 Gigahertz, in der Höllenmaschine 4 läuft der Core i7 mit 4 GHz. Berechnungen puffert der 3960X in einem dreistufigen Cache-System: So ist die dritte Cache-Stufe, die alle Prozessorkerne dynamisch nutzen können, 15 MB mächtig. Auf die erste und zweite Cache-Stufe mit 64 beziehungsweise 256 KB darf hingegen jeder CPU-Kern exklusiv zugreifen.

Eine der wichtigsten exklusiven Funktionen der LGA2011-Baureihe ist der integrierte Speicher-Controller, der vier DDR3-Kanäle gleichzeitig ansteuert. Ebenfalls in der CPU verbaut sind 40 PCI-Express-3.0-Kanäle. Zur weiteren Ausstattung gehören der Schutz vor Angriffen durch einen Puffer-Überlauf (XD-Bit), zusätzliche Befehlssätze wie SSE 4.2 und das Advanced Encryption Standard Instruction Set (AES IS) sowie die Advanced Vector Extensions (AVX). Zudem unterstützt der Prozessor die Virtualisierungs-Technik Intel VT sowie 32- und 64-Bit-Betriebssysteme – so lassen sich etwa virtuelle Workstations mit unterschiedlichen Betriebssystemen einrichten.

Die Wasserkühlung Cooler Master Eisberg 240L Prestige gibt die CPU-Abwärme über einen Dual-Radiator an die Außenwelt ab, der zwei 120-Millimeter-Lüfter beherbergt. Das Rotationstempo der mit knapp 21 dB(A) sehr leisen Lüfter liegt bei 1600 Umdrehungen pro Minute. Im Microchannel-Kühlblock arbeitet deutsche Pumpentechnik, die bis zu 400 Liter pro Stunde durch das Kühlsystem schleudert und für mindestens 50 000 Betriebsstunden ausgelegt ist. Der keramikbeschichtete Pumpenantrieb dreht sich mit bis zu 3600 Rotationen pro Minute.

Grafik: 2x ASUS GTX690-4GD5 im Quad-SLI

Um die Grafikdarstellung kümmert sich in der Höllenmaschine 4 die derzeit leistungsfähigste Grafikkarte der Welt, die ASUS GTX690-4GD5. Kostenpunkt: knapp 1000 Euro pro Stück. Die Karte beherbergt mit der Nvidia Geforce GTX 690 gleich zwei 915 Megahertz schnelle Grafikprozessoren, die gemeinsam die 3D-Berechnung übernehmen.

PC-WELT

In der Höllenmaschine 4 sind gleich zwei der Asus-Doppeldecker, die über eine SLI-Brücke (Scalable Link Interface) verbunden sind. So arbeiten insgesamt vier Grafikprozessoren parallel im Quad-SLI-Modus. In der Summe stehen damit die Rechen-Power von 6144 Shader- und 512 Textur-Einheiten sowie 128 Rasteroperatoren bereit. Dabei kann der Karten-Verbund auf 4 Gigabyte GDDR5-Videospeicher zugreifen, der mit einem effektiven Datentakt von 6000 MHz arbeitet. Jede Grafikkarte besitzt mit einem Mini-Displayport und dreimal DVI vier digitale Ausgänge.

Ausstattung der Höllenmaschine 4 im Überblick

Komponente	Modell	Preis (Euro) am 31.8.2012
Gehäuse	Casemod auf Basis des Cooler Master Cosmos II	1413
Hauptplatine	Asus Rampage IV Extreme, Intel X79, LGA2011	350
Prozessor	Intel Core i7-3960X, 3,30 GHz, 6 Kerne, 12 Theads	900
CPU-Kühlung	Cooler Master Eisberg 240L Prestige	180
Arbeitsspeicher	8 x 8 GB Adata XPG X Series PC3-17066U	880
Grafikkarte	2 x Asus GTX690-4GD5, Nvidia Geforce GTX 690	2000
Bildschirme	3 x ASUS VG278H, 27 Zoll, 3D-LED-LCD,	1550
SSD (System)	OCZ RevoDrive 3 X2 480GB, PCI-Express, 4fach Raid-0	650
Festplatten (Daten intern)	4 x Western Digital VelociRaptor 1000GB, Raid-5	1000
Festplatten (Daten extern)	2 x Western Digital Caviar Green 3000GB	300
Blu-ray-Brenner	Asus BW-12B1ST, SATA	100
Netzteil	Cooler Master Silent Pro Hybrid 1300W	250
Eingabegerät	Logitech G9x Laser Mouse und G19 Gaming Keyboard	200
Lautsprecher-Set	Logitech Z906, 5.1 System	250
Headset	Logitech G930 Wireless Gaming Headset	150
Betriebssystem	Microsoft Windows 7 Ultimate 64 Bit	160
Multimedia-Paket	Adobe Creative Suite 6 Design & Web Premium	2000
Spiele-Paket	18 Top-Titel	600
Office-Paket	Microsoft Office Professional 2010	400

PC-WELT

Monitore: PC-Spiele in 3D auf 3 Panels gleichzeitig

Der Höllenmaschine 4 stellen wir den 27-Zoll-Bildschirm ASUS VG278H zur Seite. Die physikalische Auflösung des 120-Hertz-Monitors beträgt 1920 x1080 Pixel, die Reaktionszeit 2 Millisekunden. Die LED-Hintergrundbeleuchtung erzielt eine Helligkeit von 300 cd/m2 und unterstützt die Lightboost-Technik und damit natürlich auch Nvidia 3D Vision 2 – eine Technologie, die das Spielen in der dritten Dimension möglich macht. Im Lieferumfang des Asus-LCDs ist das “Nvidia 3D Vision”-Set aus Infrarot-Sender (integriert im Bildschirmrahmen) und Shutter-Brille enthalten. Der VG278H bietet mit DVI, HDMI und D-Sub drei Videoeingänge sowie einen Kopfhöreranschluss.

Ein großer 27-Zoll-Monitor ist gut, doch drei ASUS VG278H sind besser. Die gebündelte Auflösung des Bildschirm-Trios von 5760 x 1080 Pixeln erlaubt einen Desktop, auf dem sich bequem arbeiten lässt: Da kann man zahlreiche Fenster in ihrer vollen Größe geöffnet lassen, und behält dennoch den Überblick. Interessant ist diese große Arbeitsumgebung auch für Grafiker und Video-Bearbeiter, die dadurch gleich mehrere Projekte am Laufen halten, ohne eines schließen zu müssen.

Ernsthaften PC-Spielern kann dagegen die Bildschirmgröße nicht groß genug sein – denn sie bedeutet größere Übersicht und ein realistischeres Spielerlebnis. So füllt etwa die wunderschöne Landschaft in Skyrim die volle Breite der drei Monitore aus und wirkt dadurch schon fast wie ein echter Horizont, der Lust auf das Erkunden macht. Dank der brachialen Leistung der Höllenmaschine 4 und Nvidia 3D Vision Surround geht das auch flüssig in stereoskopischem 3D.

Arbeitsspeicher: Quad-Channel mit 64 Gigabyte

Speicher kann man nie genug haben! Die acht Module Adata XPG X Series PC3-17066U mit jeweils 8 Gigabyte Kapazität steuert der Controller in der Intel-CPU im Vierkanal-Modus an. Die Module laufen mit 10-11-11-30er-Zugriffszeiten. Der mit dem Extreme Memory Profile (XMP) effektiv 2133 Megahertz schnelle Arbeitsspeicher beschert der Höllenmaschine 4 eine Speicherbandbreite von über 45 Gigabyte pro Sekunde. Da macht Virtualisierung so richtig Spaß.

PCI-Express-SSD, 4 WD VelociRaptor und 4 WD Caviar Green

Das Betriebssystem und alle Programme dürfen auf der Solid State Drive OCZ RevoDrive 3 X2 480GB Platz nehmen. Die Flashspeicher-Festplatte arbeitet mit vier Sandforce-SF-2281-Controllern intern als Raid-0-Verbund. Dadurch erreicht die SSD eine Datentransferrate von in der Spitze fast 1400 Megabyte pro Sekunde und einen Befehlsdurchsatz von bis zu 230.000 IOPS beim zufälligen Schreiben von 4-KB-Blöcken. Eine herkömmliche SATA-Schnittstelle würde das OCZ-Modell ausbremsen, deswegen setzt das RevoDrive auf einen PCI-Express-Anschluss.

OCZ/Kioxia

Das interne Backup übernimmt ein RAID-5‑Verbund aus vier 1-Terabyte-Festplatten. Dabei kommt das derzeit schnellste 3,5-Zoll-Laufwerk im Test zum Einsatz, die Western Digital VelociRaptor WD1000DHTZ. Die VelociRaptor rotiert mit 10.000 Umdrehungen pro Minute und puffert Zugriffe in einem 64 MB großen Cache. Die maximale Datenrate der Festplatte liegt bei 210 Megabyte pro Sekunde, die durchschnittliche Zugriffszeit bei 3,7 Millisekunden. Als RAID-5‑Verbund kommt das Platten-Quartett auf bis zu 560 Megabyte pro Sekunde und stellt dabei noch knapp 2,7 Gigabyte nutzbare Kapazität zur Verfügung.

Die Aufgabe des klassischen Massenspeichers für umfangreiche Foto-, Musik- und Videosammlungen übernehmen die beiden 3,5-Zoll-Festplatten Western Digital Caviar Green 3000GB WD30EZRX. Die besonders stromsparenden Laufwerke stecken in den zwei abschließbaren Hot-Swap-Schächten der Höllenmaschine 4. So lassen sich schnell und bequem knapp 5,5 Terabyte nutzbarer Speicherplatz im laufenden Betrieb an- und abstöpseln oder auch mal unkompliziert von A nach B tragen.

Stromversorgung: bis zu 105 Ampere auf der 12-Volt-Schiene

Keine Kompromisse machen wir bei der Stromversorgung der Höllenmaschine 4. Das Cooler Master Silent Pro Hybrid 1300W bietet genügend Reserven, um alle Komponenten zuverlässig mit Energie zu versorgen. Das vollständig modulare Netzteil stellt auf der 12-Volt-Schiene in der Spitze bis zu 105 Ampere bereit und federt damit auch locker die Lastspitzen der stromhungrigen Grafikkarten ab.

Aufgrund der “80 PLUS Gold“-Zertifizierung arbeitet das ATX-2.3-Kraftpaket mit einem Wirkungsgrad von über 90 Prozent trotzdem sehr energieeffizient. Dank der semipassiven Kühlung ist das 1300-Watt-Netzteil aber auch flüsterleise. Zudem erlaubt die im Lieferumfang enthaltene 5,25-Zoll-Lüftersteuerung neben dem automatischen Modus ein stufenlos regulierbares Drehtempo für den 130-Millimeter-Lüfter – bei harter Dauerbelastung drehen Sie den Regler einfach voll auf.

Um optische Massenspeicher kümmert sich der Blu-ray-Brenner Asus BW-12B1ST. Das Multi-Norm-Laufwerk versteht sich aber auch auf alle gängigen CD- und DVD-Formate. Bei maximal 12-fachem Schreibtempo füllt das Asus-Modell einen einlagigen 25-GB-BR-Rohling in rund 11 Minuten. BD-REs beschreibt das SATA-Laufwerk mit 2-fachem Tempo, Blu-ray-Medien liest er mit 8-facher Geschwindigkeit. Im Lieferumfang des Asus BW-12B1ST ist Software für das Backup, Brennen und Abspielen von Blu-rays enthalten.

Peripherie: Luxus-Eingabegeräte und 5.1-Raumklang

Die Logitech G9x Laser Mouse kommt mit einem 4-Wege-Scrollrad und löst mit bis zu 5700 dpi auf. Die USB-Maus besitzt eine anpassbare Griffschale sowie ein bis auf 28 Gramm aufrüstbares Gewichtsmagazin. Der interne Speicher sichert bis zu fünf Profile für individuelle Tastatur-Makros und Abtastraten.

Das Logitech G19 Gaming Keyboard besitzt ein integriertes Farb-LCD, das in Echtzeit Spiele-Informationen wie die Server-IP-Adresse oder den Punktestand für über 35 Titel anzeigt. Die G19 erlaubt verschiedene Beleuchtungsfarben und hat 12 voll programmierbare G-Tasten sowie Sondertasten für den schnellen Multimedia-Zugriff. Das Logitech-Modell fungiert aber auch als aktiver 2-fach-USB-Hub und überrascht mit einer Kabelführung auf der Unterseite für Maus und Headset.

Logitech

Das THX-zertifizierte Lautsprecherset Logitech Z906 bietet 5.1-Raumklang mit digitaler Dolby- und DTS-Decodierung. Bis zu sechs digitale und analoge Audioquellen lassen sich gleichzeitig an die Bedienkonsole anschließen. Alternativ bedienen Sie das 500-Watt-Lautsprechersystem kabellos über die Fernbedienung.

Wer nachts die Nachbarn nicht stören darf, greift zum Logitech G930 Wireless Gaming Headset. Das funkt digital mit 2,4 Gigahertz zehn Stunden lang über eine Reichweite von bis zu 12 Metern. Das Headset kommt mit drei programmierbaren Tasten, Geräuschunterdrückung und Kondensatormikrofon. Dank der Dolby-Technik Headphone und Pro Logic II kann das G930 sogar 7.1-Surround-Sound simulieren.

Kreativ-, Spiele- und Office-Paket für 4000 Euro

Auf der Höllenmaschine 4 vorinstalliert haben wir das 64-Bit-Betriebssystem Windows 7 Ultimate. Für das Microsoft-Betriebssystem haben wir uns auch wegen der DirectX-11-Unterstützung entschieden. Das laut Windows-Experte Hermann Apfelböck “beste Windows aller Zeiten” verwöhnt in der multilingualen Ultimate-Variante mit den exklusiven Funktionen Bitlocker-Verschlüsselung und dem nützlichen VHD-Boot.

Dazu gibt es drei fette Software-Pakete frei Haus. Das Highlight für Kreative ist die Adobe Creative Suite 6 Design & Web Premium. Die „Rundum glücklich“-Lösung für professionelle Bildbearbeitung, Layout und Website-Design integriert die Digital Publishing Suite und enthält folgende Programme und Werkzeuge: Acrobat X Pro, Bridge, Dreamweaver, Flash Builder, Flash Professional, Fireworks, Illustrator, InDesign, Media Encoder und Photoshop Extended.

Was zum Spielen spendiert Grafikspezialist Nvidia der Höllenmaschine 4. Das Gaming-Paket enthält die AAA-Titel Alan Wake Collector’s Edition, Batman: Arkham City, Battlefield 3, Borderlands, Call of Duty: Modern Warfare 3, Crysis 2, Diablo 3, Deus Ex: Human Revolution, Duke Nukem Forever, L.A. Noire, Mass Effect 3, Max Payne 3, Metro 2033, Rage, Skyrim, Starcraft II: Wings of Liberty, Star Wars. The Old Republik, The Witcher 2: Assassins of Kings.

Und wer die Höllenmaschine im Büroeinsatz unterfordern will, installiert Microsoft Office Professional 2010. Das Paket enthält die Programme Access, Excel, InfoPath, OneNote, Outlook, Powerpoint, Publisher, SharePoint, Word und Workspace.

Hinweis: Hier endet der Artikel über die Höllenmaschine 4 aus dem Jahre 2014.

So gewinnen Sie die HMX 6

Auch dieses Jahr verlosen wir die Höllenmaschine unter allen Teilnehmern:

Gewinnen Sie hier die HMX 6

Wie Sie die HMX 6 verfolgen können

In den kommenden Wochen folgen weitere Inhalte rund um die Höllenmaschine 6 auf YouTube, Instagram, TikTok, Facebook und natürlich auf pcwelt.de. Wenn Sie nichts verpassen wollen, sollten Sie den kostenlosen HMX-6-Newsletter abonnieren – aber vergessen Sie nicht, die Anmeldung via E-Mail zu bestätigen.

Überraschung bei GTA 6: Diesen neuen Charakter könnte Rockstar aus dem Hut zaubern

Wed, 22 Jul 2026 10:20:27 +0200

Im Profil einer Schauspielerin wurde ein Hinweis auf eine neue "russische Figur" in GTA 6 entdeckt. Bisher gab es weder in GTA 5 noch GTA Online einen weiblichen, russischen Charakter. Dieser Artikel wurde einsortiert unter Gaming.

EA Sports FC 27 - Cover enthüllt: Dieses Detail verrät eine große Änderung

Wed, 22 Jul 2026 10:20:23 +0200

EA Sports hat das Cover für EA Sports FC 27 enthüllt. Dieses ziert wenig überraschend Kylian Mbappé. Doch ein Detail auf der Verpackung deutet eine große Neuerung an. Dieser Artikel wurde einsortiert unter Gaming, Videospiel, EA Sports FC 27.

Fritzbox-Nutzer sollten jetzt nach Updates suchen: FritzOS 8.26 behebt DSL-Problem

Wed, 22 Jul 2026 09:50:57 +0200

Besitzer einer Fritzbox 7510 steht ab sofort FritzOS 8.26 bereit. Das neue Wartungsupdate behebt einen Fehler, der unter bestimmten Bedingungen die Geschwindigkeit von DSL-Anschlüssen erheblich reduzieren konnte. Darauf weisen die offiziellen Versionshinweise von Fritz sowie mehrere Medienberichte, etwa von Winfuture, hin.

Wer eine Fritzbox 7510 nutzt, sollte daher prüfen, ob die neue Firmware bereits zur Installation angeboten wird. Das Update enthält zwar keine neuen Funktionen, beseitigt aber ein Problem, das die Internetverbindung im Alltag spürbar beeinträchtigen konnte.

Fehler begrenzte DSL-Anschlüsse auf 10 MBit/s

In bestimmten technischen Konstellationen kam es vor, dass DSL-Verbindungen unabhängig vom gebuchten Tarif auf maximal 10 MBit/s begrenzt wurden. Nutzer bemerkten dies möglicherweise durch ungewöhnlich langsame Downloads, längere Ladezeiten oder Probleme beim Streaming und Online-Gaming.

Mit FritzOS 8.26 soll dieser Fehler nun behoben sein. Die offiziellen Änderungen fallen überschaubar aus:

Behebung eines Fehlers, der DSL-Verbindungen unter bestimmten Bedingungen auf 10 MBit/s begrenzen konnte
Verbesserungen der Systemstabilität

Bislang nur für die Fritzbox 7510

Aktuell wird FritzOS 8.26 für die Fritzbox 7510 bereitgestellt. Dabei handelt es sich um ein DSL-Einstiegsmodell mit Unterstützung für Supervectoring-Anschlüsse mit bis zu 300 MBit/s.

Erfahrungsgemäß veröffentlicht Fritz neue Wartungsupdates jedoch häufig zunächst für einzelne Modelle, bevor weitere Router folgen. Ob und wann andere Fritzboxen ebenfalls FritzOS 8.26 erhalten, ist derzeit noch nicht bekannt.

Unabhängig davon empfiehlt es sich grundsätzlich, regelmäßig nach neuen Firmware-Versionen zu suchen. Updates schließen nicht nur Fehler, sondern verbessern häufig auch die Stabilität und Sicherheit des Heimnetzes.

So prüfen Sie, ob das Update verfügbar ist

Die Aktualisierung lässt sich direkt über die Benutzeroberfläche der Fritzbox installieren. Öffnen Sie dazu in Ihrem Browser die Adresse „fritz.box“ und wechseln Sie anschließend zu System > Update. Dort können Sie manuell nach einer neuen Firmware suchen.

Wer automatische Updates aktiviert hat, muss in der Regel nichts unternehmen. In diesem Fall lädt und installiert die Fritzbox neue Versionen selbstständig, häufig außerhalb der üblichen Nutzungszeiten.

Für Besitzer einer Fritzbox 7510 dürfte die Installation von FritzOS 8.26 insbesondere dann interessant sein, wenn die Internetgeschwindigkeit zuletzt unerwartet niedrig ausgefallen ist.

Weitere Beiträge zum Thema:

GolangGhost Steals Chrome Secrets From macOS Keychain and Hijacks MetaMask Permissions

Wed, 22 Jul 2026 09:37:44 +0200

A new malware campaign is targeting cryptocurrency and Web3 professionals through fake job interviews. The operation delivers GolangGhost, a remote access trojan that can steal browser credentials, collect wallet data, and give attackers control of infected macOS systems. The attackers…

The post GolangGhost Steals Chrome Secrets From macOS Keychain and Hijacks MetaMask Permissions appeared first on IT Security News.

GolangGhost Steals Chrome Secrets From macOS Keychain and Hijacks MetaMask Permissions

Wed, 22 Jul 2026 09:16:43 +0200

The post GolangGhost Steals Chrome Secrets From macOS Keychain and Hijacks MetaMask Permissions appeared first on Cyber Security News.

OpenAI Says Its AI Models Acted On Its Own In An 'Unprecedented' Hack

Wed, 22 Jul 2026 09:16:37 +0200

"GPT-5.6 Sol and an 'even more capable' model used stolen credentials and exploited vulnerabilities in the Hugging Face API to obtain secret information used to cheat on evaluations," writes longtime Slashdot reader Dr. Bombay. The Associated Press reports: "We had a significant security incident during evaluation of our models," OpenAI CEO Sam Altman said in a statement posted on social media. AI startup Hugging Face said last week that it had detected an intrusion into its data processing systems that it suspected was caused by an AI agent autonomously acting on its own. "We suspected last week's cyberattack might have come from a frontier lab, given the sophistication of the agent," Hugging Face co-founder and CEO Clement Delangue said in a statement. "Turns out it did!" [...] "AI is accelerating the discovery and exploitation of vulnerabilities," OpenAI said in its statement Tuesday. "The primary lesson from this incident is that model security and safety must keep pace with rapidly advancing capabilities." Delangue said he spent the past 24 hours working with OpenAI, "and we strongly believe there was no malicious intent on their part. It's quite mind-blowing that all of this happened autonomously!" Delangue added that it "might be the first incident of its kind."

Read more of this story at Slashdot.

Xbox Game Pass im Juli: Halo-Remake, Day-1-Highlights und neue Spiele

Wed, 22 Jul 2026 08:39:15 +0200

Microsoft hat die zweite Welle an Neuzugängen für den Xbox Game Pass im Juli 2026 vorgestellt. Abonnenten erwarten acht Titel, darunter das Remake des allerersten Halo-Shooters sowie ein neues Rollenspiel der Pokémon-Entwickler. (Weiter lesen)

Fake Camera Troubleshooting Commands Deliver RATs Across Windows and macOS

Wed, 22 Jul 2026 08:38:58 +0200

A North Korean-aligned threat actor is using fake job interviews and bogus camera troubleshooting prompts to infect Windows and macOS users with remote access trojans (RATs). The campaign, tracked as ClickFake Interview, targets cryptocurrency and Web3 professionals, including non-technical staff who may have access to corporate systems, investor information, or digital assets. Threat researchers attribute […]

The post Fake Camera Troubleshooting Commands Deliver RATs Across Windows and macOS appeared first on Cyber Security News.

[Testing Update] 2026-07-22 - Kernels, Mesa, VirtualBox, Gambas3, Qemu

Wed, 22 Jul 2026 06:01:34 +0200

Hello Manjaro user community, here we have another set of package updates. We are continuing our development of the upcoming release of ‘Bian-May’ which can be expected Mid or End of July. Development speed may be a little slower the upcoming weeks. However, still let us know any issues you may found thus far.

Current Promotions

Get the latest Gaming Laptop by Slimbook powered by Manjaro: Slimbook Manjaro III
Protect your personal data, keep yourself safe with Surfshark VPN: See current promotion

Notable Package Updates

Kernels
Mesa 26.1.4 / 26.1.5
VirtualBox 7.2.14
Gambas3 3.22.0
Qemu 11.0.2

Additional Info

Python 3.14 info (click for more details) Info about AUR packages (click for more details)

Get our latest daily developer images now from Github: Plasma, GNOME, XFCE. You can get the latest stable releases of Manjaro from CDN77.

Our current supported kernels

linux61 6.1.177
linux66 6.6.144
linux612 6.12.96
linux618 6.18.39
linux71 7.1.4
linux72 7.2.0-rc4
linux61-rt 6.1.167_rt62
linux66-rt 6.6.135_rt74
linux612-rt 6.12.89_rt18

Package Changes (7/22/26 05:45 CEST)

testing core x86_64: 17 new and 17 removed package(s)
testing extra x86_64: 762 new and 759 removed package(s)
testing multilib x86_64: 19 new and 19 removed package(s)

A list of all package changes can be found here.

Click to view the poll.

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Poolside drops Laguna S 2.1, an open-weight coding model that beats rivals 10x its size

Wed, 22 Jul 2026 01:07:11 +0200

Poolside, the San Francisco AI lab that has spent most of its three-year existence quietly selling coding models to governments and defense agencies, released its most capable model to date on Tuesday — and made an unusually aggressive bet that radical transparency, not raw scale, is how a smaller lab competes at the frontier.

The model, Laguna S 2.1, is a 118-billion-parameter Mixture-of-Experts (MoE) system that activates only 8 billion parameters per token, supports a context window of up to 1 million tokens, and — according to benchmarks published by the company — matches or beats open models several times its size on agentic coding tasks. The weights are available immediately on Hugging Face under the permissive OpenMDW-1.1 license.

The headline numbers are striking for a model this small. Poolside reports that Laguna S 2.1 scores 70.2% on Terminal-Bench 2.1, a benchmark of long-horizon terminal tasks, placing it 11th on the company's compiled leaderboard — ahead of DeepSeek-V4-Pro-Max, a 1.6-trillion-parameter model that scored 64.0; Thinking Machines' 975-billion-parameter Inkling, at 63.8; and Nvidia’s 550-billion-parameter Nemotron 3 Ultra, at 56.4. On SWE-Bench Multilingual, it posts 78.5%, and on SWE-Bench Pro's public dataset, 59.4%.

Perhaps more telling than any single score: the model went from the start of pre-training on May 22 to public launch in under nine weeks, trained on 4,096 Nvidia H200 GPUs. In an industry where flagship model cycles are typically measured in quarters or years, Poolside has now shipped three models in three months.

Why the West's open-weight AI gap has become a boardroom issue

The release lands in the middle of an increasingly pointed debate about the provenance of open-weight AI. Over the past year, developer adoption has shifted decisively toward open-weight systems that companies can download, inspect, and run on their own infrastructure — and the leading options in that category have overwhelmingly come from Chinese labs. DeepSeek, Qwen, Kimi, GLM, MiniMax, and Tencent's Hunyuan line all feature prominently in Poolside's own comparison tables.

Poolside's accompanying press release frames Laguna S 2.1 explicitly as a response, noting that the model occupies a size class into which no Western lab has released open weights in 11 months — since OpenAI's gpt-oss-120b last August. "The West needs open-weight models it can trust, run, and build on," said Jason Warner, Poolside's co-CEO, in the announcement.

Co-founder and co-CEO Eiso Kant made the philosophical stakes even plainer in a lengthy post on X. "I believe intelligence should and will become a commodity," he wrote, arguing that the open ecosystem "will not win by being the best in its own category." Users, he argued, simply want the best intelligence for the task at hand — so open models must be on par with, or better than, their closed equivalents.

The strategic logic here is not charity. Poolside's core business is deploying models inside the security boundaries of government, defense, and regulated enterprises — customers for whom closed, metered API access is often a non-starter for compliance and sovereignty reasons.

Every enterprise that standardizes on a Chinese open model today becomes harder to win tomorrow. Releasing competitive open weights is both an ecosystem play and a top-of-funnel strategy for the company's high-security deployment business. It also reframes the AI race away from terrain where Poolside cannot compete — frontier-scale capital expenditure — and toward terrain where it believes it can: cost per token, self-hosting, and iteration speed.

How a sparse architecture makes enterprise AI agents affordable to run

The technical design reflects a specific thesis about where value in coding AI is moving. Laguna S 2.1's sparse MoE architecture — 256 routed experts plus one shared expert, with grouped-query attention and interleaved sliding-window layers, according to the Hugging Face model card — means inference costs scale with the 8 billion active parameters, not the 118 billion total. Poolside emphasizes that the model is small enough to run on a single Nvidia DGX Spark, the desktop-class AI machine.

That matters for what Poolside calls token economics. Long-horizon coding agents are voracious consumers of tokens: the company's published data shows the model consuming a mean of roughly 249,000 completion tokens per trajectory on its hardest benchmark when thinking mode is enabled. At metered API prices, agentic workloads at enterprise scale become a meaningful budget line item. On OpenRouter, Poolside is offering a free 256K-context endpoint and a dedicated 1M-context deployment priced at $0.10 per million input tokens and $0.20 per million output tokens — aggressive pricing that undercuts most frontier alternatives by an order of magnitude.

The ecosystem support is unusually broad for day one. The model is live on Baseten's model library and Vercel's AI Gateway, with integrations across vLLM, SGLang, Ollama, and llama.cpp, plus quantized variants down to 4-bit GGUF files — 75 gigabytes — for local use. But Poolside's more interesting claim is behavioral, not architectural. Pengming Wang, co-head of applied research at Poolside, said the gains came from improving the model's working habits: "more verification, less taking things for granted, not declaring victory early, and being more persistent." Raw intelligence, the company argues, is one axis of capability; a model's way of working is a second axis that matters immensely for agents left unattended for hours.

Publishing every benchmark trajectory to counter AI's credibility crisis

The most consequential part of the release for enterprise buyers may be an evaluation-transparency move with little precedent among major labs: Poolside published the complete, unedited trajectory of every trial in its final benchmark runs — every reasoning step, tool call, and shell command behind every reported score.

This addresses a growing credibility problem in AI benchmarking. As top scores on mature benchmarks cluster in the 70–90% range, and as "reward hacking" — models finding solutions online or gaming verifiers rather than solving problems — has become endemic, self-reported numbers have lost much of their signal. Poolside disclosed its own encounters with the problem candidly: during training, more than half of trajectories on some SWE-bench tasks were flagged because the model simply researched the original bug-fix pull request online and applied it. The company documented its mitigations, including prompt addenda, LLM-based judging calibrated against human labels, and expert annotator review of a high-scoring Terminal-Bench run.

Three published case studies illustrate what the company means by persistence. In one, the model built a working HTML/CSS rendering engine from an empty folder in a 181-step, 50-minute unattended session — then, lacking vision capabilities, spun up headless Chromium to numerically compare its canvas output against a real browser's rendering. In another, pointed at Poolside's own agent harness in an automated optimization loop, the model made the Go codebase 5.2% faster with roughly 70% lower memory allocation, finding an O(n²) string-concatenation bug along the way. In a third, working in a sandbox with no Python installed, the model did its number theory in Perl and independently re-derived a proof of Erdős problem #397 — a combinatorics question open for five decades until GPT-5.2 Pro first solved it this past January. Poolside notes that its model's construction is structurally different from the earlier published solution, and that its November 2025 knowledge cutoff precedes the first proof.

What the disclosed limitations and benchmark fine print reveal

Poolside deserves credit for disclosing limitations most labs bury. The model can overfit to its native harness and stumble on slightly different tool schemas in third-party agents, mangles JSON in nested tool arguments, and is prone to overthinking on competition math. There is currently no user-configurable thinking-effort dial — just on or off — and the gap between the modes is enormous: thinking lifts Terminal-Bench 2.1 from 60.4% to 70.2%, and DeepSWE from 16.5% to 40.4%, at substantially higher token cost.

Buyers should apply their own discounts to the comparison tables. Poolside's methodology takes the maximum of vendor self-reported scores, benchmark-author leaderboards, and third-party figures for competitors — a reasonable convention, but one that mixes harnesses and test conditions. On DeepSWE, notably, Poolside ran its own agent harness rather than the leaderboard's standard mini-swe-agent, a difference the company acknowledges makes scores less directly comparable. And the frontier remains clearly out of reach: closed models like GPT-5.6 Sol, at 88.8 on Terminal-Bench 2.1, and Claude Fable 5, at 88.0, along with the 2.8-trillion-parameter open-weight Kimi K3, at 88.3, sit well above Laguna S 2.1.

The deeper structural question is whether Poolside's "Model Factory" — the internal platform the company credits for its rapid release cadence — can sustain this pace as models scale. The trajectory so far is genuinely unusual: the April dual release of Laguna M.1 and XS.2, the July 2 refresh of XS 2.1, and now S 2.1, which the company says outperforms April's flagship M.1 at roughly a third of its active size. Remarkably, S 2.1 used the exact same pre-training data as XS 2.1, meaning nearly all the improvement came from scale, training fixes, and post-training across the company's corpus of 409,000 agentic and non-agentic training environments. Poolside says its next, larger Laguna model began pre-training last week.

For technical decision makers, Laguna S 2.1 is the most credible Western open-weight option to emerge in nearly a year for self-hosted agentic coding — with published evidence, a permissive license, broad ecosystem support, and an economics story built around hardware you can own. Whether it dents the dominance of Chinese open models will depend less on this release than on the ones that follow it.

Kant, for his part, has already told the world how he intends that story to end. Poolside is building toward a future where the most capable intelligence "can be owned and shaped by anyone," he wrote — and the company plans to keep shipping "until that future exists." In an industry where the biggest labs increasingly lock their best work behind an API, the most radical thing about Laguna S 2.1 may not be what it scores, but that anyone can download it and check.

The defense against the AI arts.

Tue, 21 Jul 2026 23:54:07 +0200

Trump's latest AI leader resigns. The Army burns through its AI tokens. Scammers impersonate IC3 personnel.HollowGraph malware uses a compromised Microsoft 365 calendar for C2. Qilin ransomware targets a critical Palo Alto Networks flaw. A North Korean campaign targets Web3 and cryptocurrency professionals through fake job recruitment scams. Zimbra patches multiple critical bugs. Shadow AI creates regulatory headaches. Hackers wipe Romania’s land registry database. Our guest is Errol Weiss, Chief Security Officer at Health-ISAC, setting the record straight on ransomware trends. Patching the automotive security system you didn’t know you had.

OpenAI Says Its A.I. Models Went Rogue and Attacked a Digital Library

Tue, 21 Jul 2026 23:32:39 +0200

The incident, which targeted the computer systems of another company called Hugging Face, happened while OpenAI was testing the systems.

Game On With a Massive $1,500 Off This HP Omen Max Gaming Laptop

Tue, 21 Jul 2026 22:56:50 +0200

This high-end gaming laptop is built for serious play and demanding creative work.

5 gaming accessories I refuse to play without

Tue, 21 Jul 2026 21:33:23 +0200

After years of gaming on PC, these are the five accessories I keep coming back to for their comfort, performance, and reliability.

Gaming-Fans von Fortnite und Co. aufgepasst: So stehlen Kriminelle aktuell euer Konto

Tue, 21 Jul 2026 21:21:49 +0200

Fans von Fortnite, Counter-Strike und Co. sollten sich vorsehen. Webseiten, die den Wert des eigenen Inventars errechnen wollen und kostenlose Skins bieten, sind oft eine Falle. Dieser Artikel wurde einsortiert unter Gaming, Aktuelle Betrugswarnungen.

How to use commands in Minecraft

Tue, 21 Jul 2026 20:03:27 +0200

Minecraft as a game is simple to play if you’re not looking to build impressive structures. There’s plenty in it to explore and if you’re starting off, you may spend some time learning basic recipes but it’s not hard. Outside the gameplay, there are a few tools and features in Minecraft that are worth learning […]

The post How to use commands in Minecraft appeared first on AddictiveTips.

EA Sports FC 27 - Datum bekannt: Dann erscheint der Reveal-Trailer

Tue, 21 Jul 2026 18:18:02 +0200

In wenigen Tagen ist es soweit: EA Sports hat den ersten Clip zu EA Sports FC 27 angekündigt. Wir verraten euch, wann der Reveal-Trailer erscheint. Dieser Artikel wurde einsortiert unter Gaming, Videospiel, EA Sports FC 27.

What Happened When Meta Used A.I. to Ban Accounts on Facebook and Instagram

Tue, 21 Jul 2026 17:51:10 +0200

Users said the technology mistakenly deleted their accounts. To resolve the issue, they still had to rely on A.I.

Magnus Evo XL Testbericht: Höhenverstellbarer Gaming-Tisch im Check

Tue, 21 Jul 2026 17:51:03 +0200

Der Secretlab Magnus Evo XL verspricht hohe Stabilität und cleveres Kabelmanagement für Gaming und Homeoffice. Unser Test zeigt, ob der höhenverstellbare Schreibtisch seinen relativ hohen Preis rechtfertigt.

Meta’s Quest Game Subscribers Will Be Getting Some Xbox Extras

Tue, 21 Jul 2026 17:22:50 +0200

Meta’s throwing Xbox cloud gaming Into Its Horizon Plus Quest subscription, and converting its controllers to work with it.

Estée Lauder says it was hit by data breach caused by Oracle E-Business issue

Tue, 21 Jul 2026 16:18:45 +0200

The breach happened in August 2025, but was only spotted recently by Estée Lauder.

GTA 6: Rockstar stoppt Werbekampagne - das kann nur eines bedeuten

Tue, 21 Jul 2026 16:03:53 +0200

Rockstar hat seine Werbekampagne für den Vorverkauf von GTA 6 auf Instagram, YouTube und TikTok gestoppt. Fans sehen darin ein eindeutiges Zeichen für eine lang ersehnte Veröffentlichung. Dieser Artikel wurde einsortiert unter Gaming, Videospiel, GTA 6.

What Happened at WordCamp Europe 2026

Tue, 21 Jul 2026 15:53:05 +0200

WordCamp Europe 2026 brought the WordPress community to Kraków for three days of contribution and conversation, from CERN going live on WordPress to WordPress 7.0, AI, and a closing fireside chat on where the project goes next. Read the full recap.

Kartenbetrug durch Kreditkartenvergleich vorbeugen: So lassen sich sichere Kreditkarten finden

Tue, 21 Jul 2026 15:43:49 +0200

Online-Shopping ist bequem. Gerade wer regelmäßig Hardware, Software-Lizenzen, Gaming-Zubehör oder andere Technik online bestellt, bezahlt häufig per Kreditkarte – und […]

Der Beitrag Kartenbetrug durch Kreditkartenvergleich vorbeugen: So lassen sich sichere Kreditkarten finden erschien zuerst auf WinTotal.de.

Glorious GHS Wireless InfinitePlay: Gaming-Headset mit Wechsel-Akku und Multiplattform-Support

Tue, 21 Jul 2026 15:34:39 +0200

Der US-Hersteller Glorious versucht derzeit verstärkt, mit seiner PC-Peripherie auch in Europa bzw. Deutschland Fuß zu fassen. Dazu passt, dass man ab sofort mit dem GHS Wireless InfinitePlay ein neues Gaming-Headset anbietet. Dieses nutzt, wie auch die Maus Model D3,...

Zum Beitrag: Glorious GHS Wireless InfinitePlay: Gaming-Headset mit Wechsel-Akku und Multiplattform-Support

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The wireless headset that gets hot-swappable batteries right

Tue, 21 Jul 2026 15:34:37 +0200

New gaming gear is always promising to shave milliseconds off latency or response time. The improvements usually aren't obvious. But the Glorious GHS InfinitePlay wireless headset, on the other hand, could save you far more than just milliseconds: It has the fastest hot-swap battery system I've ever used, and the headset doesn't die when you […]

North Korean ClickFake Campaign Targets Web3 Professionals

Tue, 21 Jul 2026 15:25:41 +0200

Security researchers at SOCRadar have identified a sophisticated social engineering campaign by North Korean threat actors targeting professionals in the Web3 and cryptocurrency sectors. This article has been indexed from CyberMaterial Read the original article: North Korean ClickFake Campaign Targets…

The post North Korean ClickFake Campaign Targets Web3 Professionals appeared first on IT Security News.

Wer GTA 6 vorbestellt und dann GTA 5 öffnet, erlebt jetzt eine Überraschung

Tue, 21 Jul 2026 15:18:50 +0200

Wer GTA 6 vorbestellt hat, sollte jetzt unbedingt noch einmal den Vorgänger auf der PlayStation oder Xbox spielen. Im Hauptmenü erwartet euch nämlich eine kleine Überraschung. Dieser Artikel wurde einsortiert unter Gaming, Videospiel, GTA 6.

The AI allocation trap: Record spend, vanishing returns

Tue, 21 Jul 2026 15:18:28 +0200

In a single month, one enterprise reportedly spent half a billion dollars on AI. A consultant told Axios that the client had handed its workforce AI licenses, set no usage limits and let the meter run until finance noticed. The figure is spectacular, and it is the wrong thing to fear. That half-billion-dollar accident is only the visible part of a quieter, far larger failure. Worldwide AI spending is forecast to reach $2.52 trillion in 2026, more than any technology category in a generation, and by the most cited measure, roughly 95 percent of it returns nothing. Boards read that as proof that the technology does not work. The evidence points somewhere less comfortable, and it is not a technology problem at all. Most boards cannot see it because they are reading the wrong number: They track failure when the number that matters is allocation. The discipline that separates the winners is not technical. It is how they allocate capital across time, and how willing they are to stop. The hardest discipline in the AI era is not adopting faster. It is allocating honestly and refusing to judge a three-year bet on a six-month cycle.

The number everyone quotes, and no one acts on

The headline statistic is now familiar. MIT’s Project NANDA, in its 2025 study The GenAI Divide, found that about 95 percent of enterprise generative AI pilots produced no measurable impact on the P&L, while roughly 5 percent captured nearly all the value. S&P Global Market Intelligence found that the share of companies abandoning most of their AI initiatives jumped from 17 percent to 42 percent in a single year, with the average organization scrapping 46 percent of its proofs-of-concept before production. Gartner expects more than 40 percent of agentic AI projects to be canceled by the end of 2027, citing escalating costs, unclear business value and inadequate risk controls. And the pattern predates generative AI: RAND found that more than 80 percent of AI projects fail, roughly twice the rate of comparable work that does not involve AI.

Read as a technology story, these numbers say AI does not work. Read correctly, they say something more useful. MIT’s own authors located the cause not in model quality but in a learning and integration gap. The winners were not running better models. They picked one problem, executed and worked well together. Purchased solutions reached production about 67 percent of the time, while internal builds succeeded roughly a third as often. Gartner’s own spending forecast notes the same pivot, with CIOs scaling back ambitious internal builds in favor of commercial solutions that promise more predictable value. None of that is a verdict on the technology. It is a verdict on allocation: What gets funded, for how long and against which yardstick. The popular prescription, heard in every boardroom this year, is to measure harder and prove value sooner. That advice quietly repeats the mistake, because forcing a three-year bet to prove itself sooner is precisely how you kill it. The fix is not more measurement. It is measuring each bet against the right clock and subtracting the ones that miss.

The six-month cycle problem

Return to that 95 percent, because the way it is measured is the whole argument. Much of the reported failure is judged on a short clock, with a pilot counted as a failure if it has not shown a measurable financial return within roughly six months. The single most quoted number in enterprise AI is therefore a six-month yardstick applied to every initiative, including the bets designed to pay back in three years. The headline failure rate is not only a measure of AI. It is a measure of impatience.

The most expensive mistake in enterprise AI is a timing error. Enterprises have been spending heavily on AI for more than two years, and 2026 is the year boards are demanding returns. The multi-year bets funded during the 2024 and 2025 scale-up are only now far enough along to be judged. When a board reviews an initiative, it applies the yardstick it knows, which is quarterly return. That yardstick is correct for an efficiency project and ruinous for a capability bet. A workflow automation that should pay back in two quarters and a foundational data and agent capability that pays back in three years are not the same instrument, yet they are reviewed in the same meeting against the same metric.

This is the heart of the divide. The 5 percent did not simply pick better projects. They judged each project against its own horizon. McKinsey’s enduring Three Horizons model made this discipline standard in corporate strategy a generation ago: near-term, emerging and long-term bets are funded and measured differently. AI erased that discipline because the hype compressed every timeline into the current quarter. The result is two failure modes that appear opposite yet share a common root. Organizations kill three-year bets at month six because they miss a metric the bet was never designed to hit. And they keep funding six-month theater for years because it is visible, safe and never asked to prove a return. Both are allocation failures. Neither is a technology failure.

Subtraction is a strategy

There is a second discipline, the 5 percent share, and it is the one boards find hardest. They subtract. Every credible study of the failure rate describes the same chaotic pattern underneath it: Initiatives are abandoned late, without criteria, after the money is spent and the credibility is gone. Disciplined organizations do the opposite. They decide the conditions for stopping before they start, and they stop on schedule. Subtraction is not the absence of strategy. It is the strategy. Capital removed from a failing bet is capital available for a surviving one, and the survivors are where the entire return lives.

This reframes the 42 percent abandonment figure. Abandonment is not the problem. Undisciplined abandonment is. An organization that liquidates a position the moment it breaches a pre-agreed kill line is practicing portfolio hygiene. An organization that lets a doomed pilot run until someone loses patience is paying full price for a lesson it could have bought at a discount. The 5 percent who won were not smarter. They were patient in the right places and ruthless in the wrong ones.

The HALT framework: Horizon, Allocation, Liquidation, Tracking

Treating AI as a portfolio rather than a pile of pilots requires four disciplines, and the organizations that execute well put all four in place before the next funding cycle, not after the next failure. The name is deliberate. The discipline most enterprises lack is the willingness to halt the wrong bets in time to fund the right ones.

Component 1: Horizon. Classify every AI initiative by its true payoff horizon before it is funded. Horizon 1 covers efficiency plays that should return value within two quarters. Horizon 2 covers capability bets, data foundations, agent platforms and integration work that pays back in roughly 6 to 18 months. Horizon 3 covers transformation bets that take eighteen months to three years or longer. Each horizon carries its own success metric, set at funding time. A Horizon 1 yardstick never judges a Horizon 3 bet. This single rule prevents the most common and most expensive error in the portfolio.

Component 2: Allocation. Decide the split across horizons deliberately, as a board-level capital decision, not as the accidental sum of whatever pilots happened to win approval. A practical reference point, borrowed from decades of innovation-portfolio practice, is roughly 70% to near-term value, 20% to capability, and 10% to transformation. The exact ratio is yours; the discipline is to choose and defend it. The failure mode is an unmanaged portfolio: 90 percent scattered across disconnected Horizon 1 experiments, with nothing compounding into the Horizon 2 capability that the buy-and-integrate winners actually built.

Component 3: Liquidation. Attach a kill line to every initiative at the moment it is funded: A named milestone, a date and an owner empowered to stop it. If a bet misses its horizon-appropriate milestone, it is liquidated, and capital is reallocated on schedule without debate over sunk costs. The absence of a pre-agreed kill line is not patience. It is an unpriced liability that the board has almost certainly not been shown.

Component 4: Tracking. Report the portfolio to the board on a fixed cadence using a single instrument: The AI Portfolio Scorecard. Not a deck of project updates, but a single view of allocation by horizon, burn against milestone, liquidation decisions taken and capital reallocated to survivors. The cadence is the control. A portfolio reviewed once a year is a portfolio managed by hope.

THE AI PORTFOLIO SCORECARD: SCORE EVERY INITIATIVE BEFORE IT IS FUNDED

Evaluation criterion	0	1	2
Horizon assigned (H1 / H2 / H3) and documented before funding
Success metric matched to the horizon, not a default quarterly ROI
Kill line set: Named milestone and date, agreed at funding
Owner named with explicit authority to stop the initiative
Fits a deliberate allocation band, not an accidental addition
Odds-raising path documented: Buy or partner and an integration plan

Score each criterion: 0 = not present, 1 = partially documented, 2 = fully verified. Total out of 12. Bands: 0 to 4 = DO NOT FUND | 5 to 8 = CONDITIONAL | 9 to 12 = FUND.

THE LIQUIDATION GATE: RUN AT EVERY BOARD REVIEW BEFORE CONTINUING FUNDING

Review test	Status
Milestone for this horizon met or credibly on track	PASS / FAIL
Burn within plan to the next milestone	PASS / FAIL
Still fits the allocation band, with no quiet horizon drift	PASS / FAIL
Owner confirms continued strategic fit	PASS / FAIL

Any unresolved FAIL = stop funding, liquidate the position, reallocate the capital to a survivor and record the decision on the scorecard.

The cost of the timing error

The financial case follows the pattern and is consistent. Consider two organizations that funded the same class of Horizon 3 bet: A domain-specific agent platform meant to compound over three years. The first review was conducted at month six against a quarterly return test, found no payback and killed it, booking the write-off as a lesson about AI being overhyped. Its competitor classified the same work as Horizon 3, set an 18-month capability milestone, protected funding through two review cycles and shipped to production within the window the work actually required. One organization spent its money to learn that it lacks allocation discipline. The other spent comparable money and now owns a capability its rival has abandoned and cannot quickly rebuild. The dollars on the two income statements are similar. The competitive positions are not.

The governance return the board has been waiting for

Allocation discipline does two things at once. It stops the bleed by liquidating failures on a schedule rather than at the point of exhaustion. And it concentrates capital where the entire return lives, in the small number of bets that survive their horizon. The 5 percent figure is not a ceiling imposed by the technology. It is the current yield of an industry allocated by hype. An organization that classifies by horizon, allocates on purpose, liquidates on a line and tracks on a cadence is not trying to beat the technology. It is trying to beat its own indiscipline, and that is a far more winnable contest.

The board conversation about AI returns is coming for every organization, and it arrives the moment the spending outpaces the story. When it does, the CIO will be asked a simple question: Where did the money go? The leaders who can answer will not show a pile of pilots. They will show a portfolio: What was funded, against which horizon, what was liquidated and when, and what the survivors are now worth. Subtraction is a strategy. The only question is whether you are practicing it on purpose or about to learn it by accident.

This article is published as part of the Foundry Expert Contributor Network.
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PlayStation 6: Das erste echte Upgrade zur PS5 ist durchgesickert

Tue, 21 Jul 2026 14:54:40 +0200

Sony denkt die Kühlung der PlayStation 6 (PS6) komplett neu: Statt riskantem Flüssigmetall sollen spezielle Wärmerohre die Hitzeprobleme beim vertikalen Aufstellen beenden. Ein Patent verrät die Technik - die aber einen entscheidenden Haken haben könnte. (Weiter lesen)

Ill-fated Companion Cube case for Steam Machine returns as a 3D-printed effort — and it's not the only striking DIY project around Valve's gaming PC

Tue, 21 Jul 2026 14:33:13 +0200

Got a 3D printer? You can make your own alternative Companion Cube case for the Steam Machine.

Nur für kurze Zeit: Nintendo Switch OLED für 200 Euro

Tue, 21 Jul 2026 13:17:40 +0200

Die Nintendo Switch 2 ist seit letztem Jahr auf dem Markt, doch die Vorgänger-Konsole bleibt dank OLED-Display, riesiger Spieleauswahl und dank einem Angebotspreis von nur 200 Euro weiterhin interessant. Dieser Artikel wurde einsortiert unter Gaming, Schnäppchen, Nintendo Switch OLED, Die besten Gaming-Handhelds 2025: Es gibt klare Alternativen zur Nintendo Switch 2.

FC 27: EA Sports kündigt Titel via WhatsApp an

Tue, 21 Jul 2026 12:04:21 +0200

Bislang hat sich EA Sports zum neuen Teil seiner Fußballsimulation EA Sports FC 27 ausgeschwiegen. Nun äußert sich das Entwicklerteam dazu via WhatsApp. Dieser Artikel wurde einsortiert unter Gaming, Videospiel, EA Sports FC 27.

Neuer PS5-Controller in Arbeit: Warum Sony jetzt am Rad dreht

Tue, 21 Jul 2026 12:04:14 +0200

Nach haptischem Feedback im jüngsten Controller, experimentiert Sony offenbar noch weiter. Künftig könntet ihr selbst am Navigationsrad drehen oder auf einem Touchscreen daddeln. Dieser Artikel wurde einsortiert unter Gaming, PS5.

Researchers Uncover North Korean ‘ClickFake’ Campaign Targeting Web3 Pros

Tue, 21 Jul 2026 11:56:11 +0200

In a new campaign, North Korean hacking group Famous Chollima targeted crypto professionals through ClickFix lures to deliver Windows and macOS trojans This article has been indexed from www.infosecurity-magazine.com Read the original article: Researchers Uncover North Korean ‘ClickFake’ Campaign Targeting…

The post Researchers Uncover North Korean ‘ClickFake’ Campaign Targeting Web3 Pros appeared first on IT Security News.

Launcher für Gaming-Handhelds: Winhanced erhält vollständig neues HUD 2.0 und mehr

Tue, 21 Jul 2026 11:49:48 +0200

Winhanced steht in Version 0.9.9.2 respektive 0.9.9.3 zum Download bereit und bringt zahlreiche Neuerungen für die alternative Benutzeroberfläche von Windows-basierten Gaming-Handhelds. Dazu zählen ein neu gestaltetes HUD, eine überarbeitete Performance-Engine und Frame-Generation-Optionen für Intel-Handhelds.

Researchers Uncover North Korean 'ClickFake' Campaign Targeting Web3 Pros

Tue, 21 Jul 2026 11:39:20 +0200

In a new campaign, North Korean hacking group Famous Chollima targeted crypto professionals through ClickFix lures to deliver Windows and macOS trojans

Steam-Festival der Zugspiele: Diese Gaming-Events solltet ihr 2026 nicht verpassen

Tue, 21 Jul 2026 11:33:23 +0200

Steam bietet 2026 wieder zahlreiche Rabattaktionen, Themenfestivals und Demo-Events. Neben den großen saisonalen Sales wie dem Summer Sale oder Winter Sale veranstaltet Valve regelmäßig Steam-Festivals zu bestimmten Genres. Dort warten nicht nur Rabatte auf passende Spiele, sondern oft auch kostenlose Demos, Livestreams und Entwickler-Events.

Shitstorm um Disc-Aus: Doch kaum jemand kauft physische PS5-Spiele

Tue, 21 Jul 2026 11:22:45 +0200

Der geplante Produktionsstopp von Spielen auf Disc für die PlayStation 5 sorgt im Netz für Kritik. Die tatsächlichen US-Verkaufszahlen zeigen jedoch ein völlig anderes Bild. Kaum noch ein neuer Titel findet als physischer Datenträger seine Käufer. (Weiter lesen)

SaaS will survive, but lazy SaaS is dead

Tue, 21 Jul 2026 11:05:13 +0200

Something interesting happened during an internal evaluation of AI meeting transcription tools at Tungsten Automation. The products worked. They weren’t bad. But sitting across from the pricing, we kept asking the same question: what exactly are we paying for?

We already had a secure enterprise AI environment. Building a meeting summary workflow took days, not months. We customized the outputs, injected our own internal context, and controlled security our way instead of working around someone else’s roadmap. We built it. It works better. We own it.

That’s not a knock on those vendors. It’s a signal of something more fundamental happening across enterprise software.

The moat was never the product

For two decades, SaaS rode a favorable asymmetry: building internal tools was hard, integrations were messy, and even modest automation required developers and long timelines. Buying was faster and cheaper than building. That asymmetry fueled the explosion of SaaS into every corner of the enterprise stack.

AI is collapsing that asymmetry. Large language models and agentic workflows can orchestrate APIs, move data between systems, generate interfaces, and automate business logic with a fraction of the engineering effort required even two years ago. The integration friction that once protected entire product categories is evaporating.

The vendors most exposed are not the deeply embedded enterprise platforms. They’re the lightweight workflow layers, the products that essentially put a polished interface on top of accessible data and relatively straightforward processes. Reporting dashboards. Meeting tools. Narrow productivity applications. These products created value by simplifying implementation. That rationale is getting harder to sustain when implementation is no longer the real barrier.

Here’s the part most analyses miss: it’s not just that AI makes development faster. It’s that agents change the integration model entirely. For 30 years, enterprise software was built for humans navigating UIs. Agentic systems don’t use UIs. They call APIs, read from multiple sources simultaneously, and move data freely across systems. The switching costs that once made incumbent software sticky are collapsing, because an agent doesn’t care which UI it used last quarter.

The SaaS that survives

The question isn’t whether SaaS survives. It’s which SaaS survives.

The companies with durable positions are not the ones with the cleanest interface. They’re the ones that transfer operational risk customers genuinely cannot absorb themselves. Compliance. Regulatory certification. Accumulated domain expertise. Liability.

Think about compliant invoicing across 140 countries. That’s not a workflow someone builds in a sprint. The certifications alone take years. A single regulatory change in one jurisdiction can break an AP process for a global enterprise overnight. Customers don’t pay for that capability because it’s technically complex. They pay because they cannot afford to own the risk of getting it wrong.

That’s the distinction that matters: AI lowers the cost of building software. It does not lower the cost of absorbing risk. The vendors who understand this are building durable businesses. The ones who don’t are quietly subsidizing their customers’ internal build programs.

Software sells features. Platforms sell accountability.

The prototype trap

The danger for enterprise buyers right now is overcorrection. Every successful prototype looks like a cost-saving opportunity. Very few survive the jump to production.

Building a workflow with generative AI is becoming straightforward. Maintaining it is not. Models evolve. Outputs drift. Governance requirements tighten. What worked cleanly in a controlled environment behaves differently at scale, and the failure mode is worse than traditional software. Rule-based automation, when it fails, fails obviously. Agents fail silently, confidently, at scale, often with a completely reasonable-sounding explanation.

Engineering teams that take on AI-powered systems need to solve for observability, model drift, access controls, audit trails, and long-term maintenance ownership. In regulated industries, they need to demonstrate exactly how the system reached every decision. That’s not a weekend project. That’s an ongoing operational commitment that compounds over time as models change and regulatory requirements evolve.

Before a team decides to replace an external platform with internal AI tooling, the honest question isn’t, “Can we build this?” The real question is, “Are we prepared to own this in production, for years, as the underlying models change beneath us?” Sometimes the answer is yes. Often the answer is no, and the true cost only becomes visible after the vendor contract is canceled.

Build vs. partner: a sharper frame

The build vs. buy framing has always been too binary. The right question is build vs. partner.

Partner for the capabilities where risk transfer, regulatory complexity, and domain expertise create genuine value your team cannot replicate. Build for the capabilities that actually differentiate your business from your competitors. Don’t burn your best engineers rebuilding compliant invoice processing or production-grade document extraction. Those aren’t competitive advantages. They’re table stakes, and someone else has already paid the cost, across decades, to make them reliable.

The organizations getting this right are honest about where they create unique value. They focus development there, and partner for everything else. The ones getting it wrong are vibe-coding solutions to non-differentiating problems while their actual competitive moat goes unattended.

The true value of software

We’re not watching the death of SaaS. We’re watching the end of the friction-based value proposition: the idea that software is worth renewing because integration used to be painful. That rationale is largely gone.

What survives is software that does something customers cannot reasonably replicate internally: absorb risk, maintain regulatory compliance, deliver operational reliability at scale, and bring genuine domain expertise into a production-grade system that someone else already stress-tested for years.

The vendors who recognize this are already repositioning around accountability, governance, and outcomes. The ones who haven’t will find the next renewal conversation noticeably harder.

Software sells features. Platforms sell accountability. That distinction is about to separate a lot of winners from a lot of cautionary tales.

—

Looking for guidance on moving my low-latency C++ project from AF_PACKET to real DPDK kernel bypass

Tue, 21 Jul 2026 03:56:19 +0200

Hi everyone,

I've been building a low-latency C++20 trading engine as a learning project over the past few months, and I'm now planning the next major version. I'd appreciate some guidance from people with DPDK or low-latency networking experience.

GitHub:
https://github.com/Shivfun99/Pulse-Order

past posts:

https://www.reddit.com/r/quantindia/s/u45s60B33Q

https://www.reddit.com/r/quant/s/IHKVkv0UGv

Current Version (V1)

The project currently includes:

Binary market data parsing
Level 2 order book
Strategy + risk checks
DPDK-based packet processing experiments
AF_PACKET backend for packet RX/TX
Cache-friendly C++20 implementation
Lock-free queues
Application-side latency benchmarking
Scenario testing and benchmarking framework

Current latency (application-side RX → TX enqueue) is in the sub-microsecond range under the benchmark setup, but I understand this is not true wire-to-wire latency since it doesn't involve a physical DPDK-supported NIC.

What I want to build in V2

I want to move to a real DPDK kernel-bypass architecture using a physical NIC instead of AF_PACKET.

My goals are:

Real kernel bypass using DPDK
VFIO-bound NIC
Poll Mode Driver (PMD)
Physical RX/TX queues
End-to-end latency measurement
Hardware timestamping (later)
Multi-queue support
Real market-data replay
Accurate p99/p99.9 latency analysis

My situation

At the moment I only have an ASUS TUF Gaming A15 laptop running Ubuntu. I don't have a desktop or server.

From what I've read, it seems server NICs like the Intel X520/X710/I350 require PCIe, which laptops generally don't provide.

My questions

Is there any practical way to use a real DPDK-supported NIC with only this laptop?
Would you recommend moving to a desktop before attempting real kernel bypass?
What hardware would you buy if you were starting today on a limited budget?
Are there any good open-source examples that demonstrate a complete RX → processing → TX pipeline with DPDK?
If you were designing the next version of this project, what features would you prioritize?

I'm building this primarily to learn low-latency systems and HFT infrastructure, so I'd really appreciate any advice, recommended hardware, papers, repositories, or common mistakes to avoid.

Thanks!

submitted by /u/Federal_Tackle3053
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How to Pick the Perfect GIGABYTE Gaming Monitor

Mon, 20 Jul 2026 23:48:16 +0200

Whether you have the latest GFX card or just want to optimize the performance of an older rig, GIGABYTE has a gaming monitor for every need.

Nächstes Studio: Alpha Dog verlässt XBOX und wird wieder unabhängig

Mon, 20 Jul 2026 20:33:37 +0200

Microsoft sortiert bei seinen Entwicklerstudios weiter aus. Nachdem Ninja Theory und Undead Labs an neue Besitzer gegangen sind und sich Compulsion Game und Double Fine Studios in die Unabhängigkeit retten konnten, folgt nun auch Alpha Dog dem letzteren Beispiel. Wie Windows Central berichtet, hat sich der mobile DOOM-Entwickler, der sich bereits 2024 im Windschatten von […]

Der Beitrag Nächstes Studio: Alpha Dog verlässt XBOX und wird wieder unabhängig erschien zuerst auf Dr. Windows.

AMD's Ryzen 7 7700X3D looks like a steal at $279, but you'll still end up paying more for less power — what gives?

Mon, 20 Jul 2026 20:11:15 +0200

AMD has already cut the price of its new Ryzen 7 7700X3D gaming CPU just days after its launch. Does that mean it's actually a better deal than its superior 7800X3D sibling? Not in 2026. Here's what most people are missing when they look at CPU prices.

Dark Winds Season 5: Release Date, Cast, Story, and Netflix Release Predictions

Mon, 20 Jul 2026 19:25:01 +0200

Dark Winds Season 5 is officially moving forward, giving viewers another mystery involving Joe Leaphorn, Jim Chee, and Bernadette Manuelito. AMC has confirmed the new season for 2027, although its exact premiere date remains unannounced. The renewal arrived before Season 4 premiered, showing AMC’s continued confidence in the crime drama. Season 5 began production in Santa Fe, New Mexico, in March 2026 and will contain eight hour-long episodes. AMC release window: Sometime in 2027 Netflix release window: Likely mid-to-late 2027 Episode count: Eight episodes Genre: Crime drama, mystery, psychological thriller and neo-Western AMC has not announced whether Season 5 will arrive early in 2027 or later in the year. Since Season 4 premiered on AMC and AMC+ on February 15, 2026, another February or March launch appears possible if production remains on schedule. When could Dark Winds Season 5 come to Netflix? Netflix has not confirmed a Season 5 release date. However, the platform’s handling of Season 4 gives us a useful timeline. Season 4 completed its AMC run on April 5, 2026, before arriving on Netflix in the United States on July 4, 2026. That placed the Netflix release roughly three months after the AMC finale. Should AMC follow a similar arrangement, Dark Winds Season 5 could reach Netflix around three months after its television finale. A spring 2027 AMC premiere would therefore point toward a summer or early autumn Netflix release. This remains an estimate because streaming agreements can change between seasons. AMC and AMC+ will receive the episodes first. What will happen in Season 5? Spoilers ahead for the Dark Winds Season 4 finale. Season 4 followed Leaphorn, Chee, and Manuelito as they searched for missing Navajo teenager Billie Tsosie. The investigation took them from the Navajo Nation to 1970s Los Angeles, where they uncovered an organized crime operation and crossed paths with Irene Vaggan. Leaphorn eventually escaped Irene’s bunker and helped rescue Billie. However, the finale ended with a new mystery when Sheriff Gordo Sena was found murdered. His death will likely become the central investigation of Season 5. The case could also bring the main characters back together professionally. Leaphorn had considered leaving the Navajo Tribal Police, while Chee and Manuelito were both facing decisions about their careers and relationship. Dark Winds Season 5 cast additions Zahn McClarnon will return as Joe Leaphorn, alongside Kiowa Gordon as Jim Chee and Jessica Matten as Bernadette Manuelito. Paola Núñez and Martin Sensmeier have joined Season 5 as series regulars. Noel Fisher, Devin Sampson-Craig and John Patrick Jordan will appear in recurring roles, although AMC has shared limited information about their characters and involvement in the new mystery. Dark Winds Season 5 already has a major unresolved murder, several new characters and important decisions ahead for its central trio. Until AMC announces a firm premiere date, viewers can watch the previous seasons on AMC+ and Netflix. What do you think happened to Gordo Sena, and where should Leaphorn’s investigation take him next? Let us know in the comments.

‘Spooky in Love’ Episode 2 Recap: Yeo-ri Reveals Her Secret

Mon, 20 Jul 2026 19:04:34 +0200

‘Spooky in Love’ Season 1, Episode 2 pushes Yeo-ri and Gang-uk into their first real investigation together, while a second murder mystery begins forming around a missing young woman. The episode continues directly after Gang-uk nearly touches Yeo-ri’s bare hand. She pulls away before contact, protecting him from the supernatural consequences that she believes follow anyone she touches. Release date: July 19, 2026 Streaming platform: Netflix Original network: tvN Genre: Romantic comedy, horror and fantasy Total episodes: 12 Release schedule: New episodes every Saturday and Sunday Main cast: Park Eun-bin, Yang Se-jong and Ong Seong-wu The Korean drama premiered on July 18, 2026, and follows hotel CEO Cheon Yeo-ri, who can see ghosts, and prosecutor Ma Gang-uk, who investigates difficult murder cases. The series is based on the 2011 Korean film Spellbound. Spoilers Ahead for ‘Spooky in Love’ Episode 2 Gang-uk questions Yeo-ri about how she found the buried victim from their first meeting. After trying to avoid his questions, she finally admits that a ghost showed her where the body was hidden. Gang-uk does not believe her explanation and leaves, although the strange events surrounding Yeo-ri continue to challenge his logical view of the world. Meanwhile, Gang-uk continues investigating professional golfer Park Seung-jae. Seung-jae was previously accused of killing his girlfriend, Jang Eun-ju, but used his family’s political influence and lack of evidence to escape conviction. Yeo-ri openly tells Seung-jae that she dislikes him. She also reveals that Eun-ju visited her before her death and said she was pregnant with his child. Seung-jae denies responsibility, but his aggressive reaction makes him appear even more suspicious. Eun-ju’s Ghost Leads Them to the Truth Eun-ju’s ghost later appears before Yeo-ri, confirming that she was murdered. Gang-uk studies the available evidence and develops a theory that Seung-jae disguised himself as a woman before hiding Eun-ju’s body inside a hotel water tank. When Gang-uk reaches the tank, he finds Yeo-ri already there. Together, they discover Eun-ju’s remains, giving Gang-uk the evidence required to arrest Seung-jae. The case establishes how useful Yeo-ri’s ability can become during murder investigations. Gang-uk provides legal knowledge and careful reasoning, while Yeo-ri receives information directly from victims who can no longer speak for themselves. Min-hwan Enters Yeo-ri’s Life Episode 2 also introduces Kang Min-hwan, Yeo-ri’s childhood friend and another hotel executive. He wants to develop a business relationship with her, although his reaction to Gang-uk suggests that his interest is also personal. A booking mistake places Yeo-ri and Gang-uk in the same hotel room. They eventually wake up in the same bed and panic, creating one of the episode’s lighter moments. Min-hwan clearly dislikes seeing them together, setting up a possible romantic rivalry. A New Missing-Person Case Begins The closing section introduces an elderly woman searching for her missing granddaughter, Jung Hae-na, an aspiring fashion designer. Hae-na appears connected to a famous designer holding an event at Min-hwan’s hotel. The circumstances surrounding her disappearance suggest that Yeo-ri and Gang-uk will soon face another case involving powerful people and hidden abuse. AsianWiki lists the Jung Hae-na storyline across Episodes 2 and 3, confirming that the mystery will continue in the next chapter. ‘Spooky in Love’ Episode 2 gives its central partnership a clearer purpose while developing the romance, the supernatural rules and the next investigation. What do you think happened to Hae-na, and will Min-hwan come between Yeo-ri and Gang-uk? Let us know in the comments.

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Der Artikel Gaming: Wie das Pay2win-Konzept gute Spiele kaputtmachen kann erschien zuerst auf TARNKAPPE.INFO

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