AI Chip Startup Etched Eyes $20 Billion Valuation

Artificial intelligence chip startup Etched is reportedly preparing to quadruple its valuation to around $20 billion.

As The Wall Street Journal (WSJ) reported Friday (July 17), sources familiar with the matter say the company is capitalizing on a soaring market for venture capital investments in AI startups, and is also raising capital at a $10 billion valuation in a separate round led by Sequoia Capital .

WSJ noted that these types of back-to-back funding have become more common in Silicon Valley during the AI boom. Companies are frequently selling stakes at one valuation and then quickly raising more money at much higher prices, which the report calls a sign of the bargaining power companies have over investors racing to invest in the leading AI firms.

According to the report, Etched has said it is developing a chip for running AI models, otherwise known as inference . The company website says Etched is testing its initial chip design and working to validate its first product to meet $1 billion in demand from clients.

WSJ added that although Nvidia is the leading vendor of AI chips, a slew of startups is trying to compete following the success of Cerebras Systems and Groq. Many of the new startups are developing chips tailored for inference, while Nvidia’s dominance is based in the ability of its graphics processing units, or GPUs, to train AI models.

Etched was launched in 2022 by a trio of Harvard dropouts: Gavin Uberti , Chris Zhu and Robert Wachen , the report added. Investment firm Stripes, Peter Thiel, Ribbit Capital and Primary Venture Partners are all among its early backers.

Meanwhile, PYMNTS wrote earlier this year that the framing of the AI story as an “ arms race” overlooks another, more difficult, aspect: demand.

This came after a series of developments suggesting that the next stage in AI’s evolution could depend less on how much capability technology companies are able to supply and more on whether ordinary organizations can generate ongoing demand inside day-to-day work.

“After all, the question facing the market is no longer simply whether frontier models can perform astonishing tasks,” that report said.

“It is whether accountants, nurses, insurance adjusters, teachers, procurement managers, financial analysts and their peers across Main Street can integrate AI into the highly specialized workflows they understand better than any Silicon Valley engineer.”

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