Top tip: If you want more of that VC money, stick some AI in your chips
This increased need for inference chips is coinciding with a projected growth in spending on AI chips for edge cases, a rather nebulous term that, in the case of Pitchbook's report, includes the PC, automotive, and industrial markets. Burke said the PC and automotive markets for AI chips grew more than 22 percent in 2022, faster than spending on such silicon for datacenters.
"Automotive and edge computing demands are driving more commercial agreements for inference-focused chips than for cloud training chips," the analyst added.Mythic, a Texas-based startup that was developing analog chips for edge AI use cases, ran out of funding from investors before it was able to generate revenue, a top executiveThen there's Graphcore, a British startup that has commercialized datacenter chips for training and inference.
had its private valuation slashed by $1 billion after losing a key deal with Microsoft, among other financial woes.she wouldn't be surprised if more chip design startups ended up getting acquired or shut down in the next year because they failed to transition fast enough from research and development to commercialization.
It's not just investors who are finding some AI chip startups still palatable in a weaker economy. Some industry veterans are also making the leap.Weifeng Zhang, Alibaba's former chief scientist of heterogeneous computing, along with Wayne Wu, the previous head of AMD's PCIe design team, and Hal Conklin, who was most recently Arm's vice president of worldwide channel sales.
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