2024 was Nvidia’s year. Its command of mindshare and market share was unequaled among tech vendors. Here’s a recap of some of the key events of 2024 that highlight just how powerful the world’s most dominant chip player is.
Nvidia teams up with Cisco
On February 6, Nvidia announced a , which Nvidia claimed would offer four times the performance of Hopper, the current architecture.
And there was new Blackwell-powered systems that, it said, will allow enterprises to build “AI factories” and data centers to drive the next wave of generative AI.
Nvidia also announced that its Nvidia MGX modular reference design platform, announced at the 2003 Computex show, now supports Blackwell products. It launched the new Nvidia GB200 NVL2 platform, a smaller version of the GB200 NVL72 introduced in March, that it said will speed up data processing by up to 18x, with 8x better energy efficiency compared to using x86 CPUs.
During his Computex keynote, CEO Jensen Huang disclosed the next generation microarchitecture, and the chips remain on schedule for delivery at the end of 2024.
Anticompetitive issues arise
The US Department of Justice announced it was initiating an investigation into anticompetitive practices by Nvidia, which analysts for its Oracle Cloud Infrastructure (OCI) Supercluster to aid large language model (LLM) training and other use cases. The company made the announcement at the CloudWorld 2024 conference. However, given the severe backlog of High-Bandwidth Memory, Oracle wasn’t likely to take delivery of the GPUs before 2026.
Elon Musk’s xAI taps Blackwell GPUs for its supercomputer
Not to be outdone by Oracle, Elon Musk and his team behind the xAI company took delivery and that due to heat from the Blackwell chips, servers needed to be redesigned to accommodate the heat. This was dismissed by Nvidia on its earnings call – and at the same time, Nvidia reported revenue gains of 17% compared to the prior quarter and 94% compared to the prior year.
AI factory designs
Nvidia released designed to bring real-time artificial intelligence to edge networks. The idea is to put AI computing closer to where sensors collect data before it is sent to larger data centers. This serves as a buffer to whittle down the data sent to data centers so only relevant data is sent down the wire for processing. This can be up to 90% or more of data collected is discarded.
Verizon, Nvidia team up for enterprise AI networking
Nvidia announced a partnership with Verizon to build AI services for enterprises that run workloads over Verizon’s 5G private network. Dubbed 5G Private Network with Enterprise AI, it will run a range of AI applications and workloads over Verizon’s private 5G network with Mobile Edge Compute (MEC), a colocated infrastructure that is a part of Verizon’s public wireless network.
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