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Etched.ai
American AI-chip startup From Wikipedia, the free encyclopedia
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Etched.ai Inc. (stylized Etched.ai) is an American semiconductor start-up that is designing Sohu, an ASIC built exclusively for transformer inference in large language models.[2] Founded in 2022 by two Harvard University drop-outs, Gavin Uberti and Chris Zhu, the company raised US$120 million in a Series A round in June 2024 to fabricate its first chips at TSMC.[1] The round was co-led by venture-capital firms Primary Venture Partners and Positive Sum Ventures, and drew angel investors such as Peter Thiel, Stanley Druckenmiller and Kyle Vogt.[3]
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History
Uberti began experimenting with compiler optimizations for AI workloads in 2022 and recruited classmate Zhu to pursue a chip start-up.[2] The pair incorporated the company in Silicon Valley and hired Robert Wachen, a former Cypress Semiconductor executive, as chief operating officer.[4]
In March 2023 the start-up closed a US$5.4 million seed round that valued the company at US$34 million.[1]
Technology
Sohu is fabricated on TSMC's 4-nanometre process node and hard-wires the matrix multiplication patterns specific to transformer inference.[2] Because the chip omits hardware needed for other neural-network types, Etched has claimed that an eight-chip Sohu server can generate more than 500,000 tokens per second on Llama-70B, versus roughly 23,000 tokens per second for an eight-GPU Nvidia H100 system.[5] Uberti has asserted that “one Sohu server replaces 160 H100 GPUs,” positioning the device as a lower-cost, lower-power competitor to Nvidia's Blackwell architecture.[4]
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Funding
Other participants in the Series A included Peter Thiel, GitHub CEO Thomas Dohmke, Balaji Srinivasan and Kyle Vogt.[6]
Reception
Trade press and analysts describe Etched as part of a “second wave” of AI accelerator companies that aim to undercut Nvidia's general-purpose GPUs.[4] CNBC characterised the firm's focus on transformers as “the biggest bet in AI,” noting that its survival depends on the continued dominance of that architecture.[3]
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External links
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