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For the past several months, companies like Microsoft, Google, OpenAI, and NVIDIA have been getting headlines for their efforts to advance generative AI hardware and software services. One major tech company, Amazon, is trying to get in on the AI conversation as well.
CNBC reports that its Amazon Web Services division has been working on two custom chips, Inferentia and Trainium, that it hopes will rival those made by NVIDIA with its Grace Hopper superchips for training large language models. NVIDIA just announced its next-gen Grace Hopper platform which should be available in 2024.
AWS is no stranger to making custom chips. It started 10 years ago with Nitro, and Amazon says there’s now at least one Nitro chip in every one of its AWS servers.
Currently, in its Austin, Texas offices, Amazon is working on new versions of its Trainium and Inferential chips. This is the company’s solution to give customers a way to train their generative AI LLMs on AWS servers, with Amazon-made chips, without having to use NVIDIA-based hardware.
Amazon says one of its biggest advantages is that AWS is already used by millions of customers, who are used to the servers and their tools. Mai-Lan Tomsen Bukovec, the VP of technology at AWS, stated:
It’s a question of velocity. How quickly can these companies move to develop these generative AI applications is driven by starting first on the data they have in AWS and using compute and machine learning tools that we provide.
While Amazon is trying to make its own chips for training LLMs, it also using some NVIDIA chips for the same purpose in its AWS servers. In July, it announced Amazon EC2 P5 instances were available for AWS users. These servers are powered by NVIDIA H100 Tensor Core GPUs.
Amazon stated to CNBC that “over 100,000” of its customers were using AWS for machine learning. While that’s just a fraction of the company’s overall AWS customer base, more and more of them could start using Amazon’s solution as generative AI expands to more industries.
