Anthropic confirmed it is building an in-house silicon team to design custom chips for its Claude AI model, a move aimed at improving performance and efficiency as demand for its services continues to rise.
In a statement to Mobile World Live (MWL), Anthropic said it “is hiring engineers with experience across the stack”.
The company stated this move will let it co-design hardware and models together, allowing Claude to run faster and more efficiently at the scale its customers need.
Anthropic told MWL the effort is not a shift away from its existing hardware partners. The company described the silicon team as the latest step in its multi-chip approach
It is building a diversified hardware stack with chips from Amazon Web Services (AWS), Google, Nvidia, and AMD, which will “remain central to how we scale”.
Reuters had previously reported Anthropic was exploring building its own chips while The Information stated the company had held talks with Samsung Electronics about possibly manufacturing them.
Business Insider cited a newly posted job listing which describes what Anthropic is looking for, which includes a “custom silicon team” with engineers spanning multiple areas of chip design and verification.
The listing, which advertises a salary range of $320,000 to $485,000, calls for candidates who can point to direct personal contribution in finalising and shipping semiconductor designs.
Building AI chips in-house is expensive and technically demanding, but the benefits include improved performance and less dependence on Nvidia.
Rival moves
Anthropic joins a growing list of AI companies pursuing custom silicon, following moves by OpenAI, Meta, Google, and Amazon.
OpenAI unveiled its first custom-built inference ASIC, Jalapeno, in June, developed in partnership with Broadcom.
In April, Meta Platforms expanded its partnership with Broadcom to jointly develop multiple generations of custom MTIA chips, building on four new generations it had unveiled in March.
Google is also developing a server chip, called Frozen v2, to improve efficiency for its Gemini AI model and separate from its existing TPUs,
During Alphabet’s Q1 earnings call in April, CEO Sundar Pichai stated the company will begin making its tensor processing units available to a select group of customers for their own data centres, a move seen as a potential challenge to Nvidia’s dominance in AI chips.
Also in April, Meta struck a deal with Amazon Web Services to use its Graviton processors for agentic AI workloads.
Amazon also has an agreement in place with Anthropic to use its Trainium chips to train and run its AI models
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