AI and Machine Learning @ I/O Recap

Posted by Lauren Usui and Joe Fernandez

and how you can apply our guidelines and tools to make sure your AI-powered products and projects are built responsibly to serve all your users.

If you are new to AI and want to get a quick overview of the technology, check out the . Our session on Generative AI reveals more about how you can easily prompt models with MakerSuite to quickly prototype generative AI applications. We demonstrate how you can use the PaLM API for prompting using examples, conversational chat interactions, and using embedding functionality to compress and compare text data in useful ways. We also showed off how to use the PaLM API in Google Colab notebooks with a simple, magical syntax. Check out this talk and sign up to request access to the PaLM API and , a Google Sheets add-on. We recently updated this tool to include anomaly detection and forecasting features. Check out the demonstration of how to predict missing data values and forecast sales with the tool. No coding required!

Simplify on-device ML applications with MediaPipe

AI is finding its way into applications across multiple platforms and , you can search thousands of open-licensed models from leading ML researchers for multiple ML platforms. Find the model you need quickly with filters for tasks, supported data types, model architecture, and more. Combine this new feature with Kaggle's huge repository of over 200K datasets and accelerate your next ML project.

Apply ML to vision and text with Keras

Lots of developers are exploring AI technologies and many of you are interested in working on computer vision and natural language processing applications. Keras released new, easy-to-use libraries for computer vision and natural language processing with . Using just a few lines of code, you can apply the latest techniques and models for data augmentation, object detection, image and text generation, and text classification. These new libraries provide modular implementations that are easy to customize and are tightly integrated with the broader TensorFlow ecosystem including TensorFlow Lite, TPUs, and DTensor.

Build ML flexibly and scalably with TensorFlow

With one of the largest ML development communities in the world, the is an end-to-end ML platform that helps you develop ML models quickly and easily, and deploy them at any scale. To help you build generative AI technology for your product or business, we've introduced Model Garden and the Generative AI Studio as part of the Vertex AI platform. Model Garden gives you quick access to the latest foundation models such as Google PaLM 2, and many more to build AI-powered applications for text processing, imagery, and code. Generative AI Studio lets you quickly prototype generative AI applications right in your browser, and when you are ready to deploy, Vertex AI and Google Cloud services enable you to scale up to hundreds, thousands, or millions of users.

Explore new resources to build with Google AI

As tools, technology, and techniques for AI development rapidly advance, finding what you need to get started or take the next step with your project can be challenging. We're making it easier to find the right resources to accelerate your AI development at and . This year at Google I/O, we shared how we've created guidelines and tools for building generative AI safely and responsibly, and how you can apply those same guidelines and tools for your own projects.

Aaannnd that's a wrap! Check out the full playlist of all the AI-related sessions we mentioned above. We are excited to share these new tools, resources, and technologies with you, and we can't wait to see what you build with them!