Data & Analytics

The AI Edge Chip Market Is on Fire, Kindled by 'Staggering' Venture Capital Funding

Dozens of startups continue to get tens of millions in venture funding to make chips for AI in mobile and other embedded computing uses. The race shows no sign of slowing down.

Fire in the microchip
Source: Petrovich9/Getty Images.

Making chips to perform AI inference on edge devices such as smartphones is a red-hot market, even years into the field's emergence, attracting more and more startups and more and more venture funding, according to a prominent chip analyst firm covering the field.

"There are more new startups continuing to come out, and continuing to try to differentiate," said Mike Demler, senior analyst with The Linley Group, which publishes the widely read Microprocessor Report, in an interview with ZDNet via phone.

Linley Group produces two conferences each year in Silicon Valley hosting numerous startups, the Spring and Fall Processor Forums, with an emphasis in recent years on those AI startups.

At the most recent event, held in October, both virtually and in person, in Santa Clara, California, the conference was packed with startups such as EdgeCortix, Flex Logix, Hailo Technologies, Roviero, BrainChip, Syntiant, Untether AI, Expedera, and Deep AI giving short talks about their chip designs.

Demler and team regularly assemble a research report titled the Guide to Processors for Deep Learning, the latest version of which is expected out this month. "I count more than 60 chip vendors in this latest edition," Demler said.

Edge AI has become a blanket term that refers mostly to everything that is not in a data center, though it may include servers on the fringes of data centers. It ranges from smartphones to embedded devices that suck microwatts of power using the TinyML framework for mobile AI from Google.

The middle part of that range, where chips consume from a few watts of power up to 75 watts, is an especially crowded part of the market, Demler said. These are usually in the form of a pluggable peripheral component interconnect express (PCIe) or M.2 card. (75 watts is the PCI-bus limit in devices.)

"PCIe cards are the hot segment of the market, for AI for industrial, for robotics, for traffic monitoring," he explained. "You've seen companies such as Blaize, FlexLogic—lots of these companies are going after that segment."

But really low-power is also quite active. "I'd say the tinyML segment is just as hot. There we have chips running from a few milliwatts to even microwatts."

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