Startup Investment Deterred by Nvidia’s AI Chip Leadership

According to investors, Nvidia’s dominant position in developing computer chips for artificial intelligence has deterred venture funding for potential competitors, resulting in an 80% decrease in the number of U.S. deals this quarter compared to last year.

The Santa Clara, Calif.-based company dominates the market for chips that work with vast amounts of language data. Generative AI models gradually become smarter by being exposed to more data, called training.

As Nvidia has become stronger in this area, it has become more difficult for companies trying to build competing chips. Seeing these startups as a riskier bet, venture capitalists are newly reluctant to offer large amounts of cash. Developing a chip design into a working prototype can cost more than $500 million, so the retreat has quickly threatened the startups’ future prospects.

“Nvidia’s continued dominance has made a really nice point about how difficult it is to break into this market,” said Greg Reichow, partner at Eclipse Ventures. “This has led to a withdrawal of investment in these companies, or at least in many of them.”

According to data from PitchBook, US startups have raised $881.4 million by the end of August. That’s $1.79 billion in the first three quarters of 2022. The number of stores has dropped from 23 to four by the end of August.

Nvidia declined to comment.

Artificial intelligence startup Mythic, which has raised a total of about $160 million, ran out of cash last year and was nearly forced to shut down, The Register reported on the technology website. But it managed to bring in a relatively modest $13 million investment several months later in March.

Nvidia has “indirectly” contributed to the general AI chip fundraising woes because investors want “home-only investments with a huge investment and a huge return,” Mythic CEO Dave Rick said.

Difficult economic conditions have added to the downturn in the cyclical semiconductor industry, Rick said.

A secret startup company called Rivos, which works on data server chip design, has recently had difficulties in obtaining financing, said two sources familiar with the company’s situation.

A spokeswoman for Rivos said Nvidia’s market position has not hindered its fundraising efforts and its hardware and software “continue to be of interest to our investors.”

Rivos has been embroiled in litigation with Apple, which has accused Rivos of stealing intellectual property rights, adding to the fundraising challenge.

DEMANDING INVESTORS

Chip startups looking to raise cash face tougher demands from investors. They require companies to have a product that is within months of launch or already generating sales, the sources said.

About two years ago, new investments in chip startups were often $200 or $300 million. That’s down to about $100 million, according to PitchBook analyst Brendan Burke.

At least two AI startups have overcome investor reluctance by disclosing potential clients or their relationships with well-known executives.

To raise $100 million in August, Tenstorrent touted CEO Jim Keller, a near-legendary chip architect who has designed chips for Apple, Advanced Micro Devices and Tesla.

D-Matrix, which is forecast to generate less than $10 million in revenue this year, raised $110 million last week with financial backing from Microsoft and a commitment from the Windows maker to test d-Matrix’s new AI chip after its launch next year.

While these chipmakers struggle in Nvidia’s shadow battle, AI software and related technology startups don’t face the same constraints. They brought in about $24 billion in funding this year through August, according to PitchBook data.

Despite Nvidia’s dominance in AI computing, the company doesn’t have an irresistible lock on the field. AMD plans to release a chip this year to compete with Nvidia, and Intel jumped on the bandwagon by buying a competing product. Sources see these as having long-term potential as alternatives to Nvidia’s chip.

There are also adjacent applications that could provide openings for competitors. For example, chips that perform data-intensive computing for predictive algorithms are an emerging niche market. Nvidia does not dominate this area and it is ripe for investment.

(Reporting by Max A. Cherney in San Francisco; Editing by Kenneth Li, Cynthia Osterman and Christian Schmollinger)