Investors claim that Nvidia’s (NVDA.O) dominance in developing computer processors for artificial intelligence has curbed venture investment for potential competitors, as seen by the 80% decrease in U.S. acquisitions this quarter compared to last year.
The Santa Clara, California-based business controls the market for processors that handle enormous volumes of linguistic data. Training is how generative AI models get gradually smarter by exposure to additional data.
Companies trying to develop rival processors have a tougher time since Nvidia has become better in this area. Venture capitalists are now reluctant to provide significant financial infusions because they see these firms as a risky gamble. The withdrawal has seriously damaged the chances of the businesses since it may cost more than $500 million to get a semiconductor concept to a functioning prototype.
Greg Reichow, a partner at Eclipse Ventures, said, “Nvidia’s continued dominance has put a really fine point on how hard it is to break into this market.” “As a result, investment in these companies—or at least into many of them—has decreased.”
According to statistics from PitchBook, American chip companies had raised $881.4 million as of the end of August. In comparison, the first three quarters of 2022 had revenue of $1.79 billion. Through the end of August, there were just four agreements, down from 23.
Nvidia opted not to respond.
Technology website The Register stated that AI chip firm Mythic, which has received over $160 million, ran out of money last year and almost had to stop operations. But many months later, it got a very small $13 million investment in March.
Because investors only demand “home run only type investments with a huge investment, huge return,” according to Mythic CEO Dave Rick, Nvidia has “indirectly” contributed to the overall fundraising difficulties for AI chips.
According to Rick, the slowdown in the cyclical semiconductor business has been exacerbated by challenging economic circumstances. According to two insiders acquainted with the company’s financial position, a covert business named Rivos, developing semiconductor designs for data servers, has had problems acquiring money lately.
According to a spokeswoman for Rivos, Nvidia’s market domination hasn’t interfered with the company’s ability to raise money, and its hardware and software “continues to excite our investors.” The difficulty in acquiring money has been made worse by Rivos’ legal spat with Apple (AAPL.O), which has accused Rivos of stealing intellectual property.
WANTED: INVESTORS
Investors’ requirements are becoming more stringent for chip firms wanting to secure capital. According to sources, they demand that businesses have a product that has either just launched or is making sales.
New investments in semiconductor firms were often $200 million or $300 million around two years ago. According to PitchBook analyst Brendan Burke, the amount has decreased to roughly $100 million.
At least two AI chip firms have managed to win over investors by highlighting their connections to high-profile executives or prospective clients.
Tenstorrent talked about its CEO Jim Keller, an almost famous chip architect who has created processors for Apple, Advanced Micro Devices (AMD.O), and Tesla (TSLA.O) to fund $100 million in August.
D-Matrix, which expects sales of less than $10 million this year, raised $110 million last week thanks to support from Microsoft and a promise from the manufacturer of Windows to test the company’s new AI chip when it became available in 2019.
While these Nvidia-shadowed semiconductor firms suffer, entrepreneurs in AI software and related fields do not have the same limitations. According to statistics from PitchBook, they received approximately $24 billion in fundraising this year up until August.
Despite Nvidia’s supremacy in AI computing, the market is not entirely under its control. Although Intel (INTC.O) acquired a competitor product, AMD (INTC.O) expects to unveil a processor that will compete with Nvidia’s this year. According to sources, they might eventually replace the chip used by Nvidia.
There are also nearby applications that might offer doors for rivals. For instance, a growing market is data-intensive processing processors for prediction algorithms. This market is open to investment and is not dominated by Nvidia.