AI Chip Startups Face Challenges Ahead

Analysts from Omdia forecast a tough year for AI chip startups. According to Omdia’s Top AI Hardware Startups Market Radar, more than 100 venture capitalists have poured over $6 billion into the leading 25 AI chip companies since 2018. However, it appears that the favorable times are coming to an end.

The ongoing global chip shortage has escalated into an inventory crisis, and the current economic downturn, along with stringent monetary policies, is making fundraising increasingly difficult. Alexander Harrowell, Principal Analyst for Advanced Computing at Omdia, notes, “The best-funded AI chip startups are under pressure to deliver the type of software support that developers expect from market leader NVIDIA.” This pressure presents a significant barrier to the introduction of new AI chip technologies.

Omdia predicts that at least one major startup will exit the market this year, likely through acquisition by a prominent chip manufacturer or a large cloud service provider. Harrowell adds, “The most probable exit strategy is through trade sales to major vendors.” Companies like Apple, with $23 billion in cash reserves, and Amazon, with $35 billion, along with other leading firms such as Intel, NVIDIA, and AMD, are well positioned to invest in such acquisitions, as they are eager to adopt customized AI chips and possess the necessary resources.

Interestingly, over half of the $6 billion invested in AI chip startups has been directed towards large-die, CGRA accelerators, intended to load entire AI models onto chips. This strategy is now under scrutiny due to the exponential growth in AI model sizes. Harrowell explains, “In 2018 and 2019, it made sense to load entire AI models into on-chip memory for low latency and to manage the input/output issues of large models. However, as these models continue to expand, scalability has become a critical concern. There is a growing need for AI processors that offer more general-purpose programmability. Consequently, the future direction of AI processors may take a different shape altogether.”

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