This paper is an update of the survey of AI accelerators and processors from past four years, which is now called the Lincoln AI Computing Survey - LAICS (pronounced "lace"). As in past years, this paper collects and summarizes the current commercial accelerators that have been publicly announced with peak performance and peak power consumption numbers. The performance and power values are plotted on a scatter graph, and a number of dimensions and observations from the trends on this plot are again discussed and analyzed. Market segments are highlighted on the scatter plot, and zoomed plots of each segment are also included. Finally, a brief description of each of the new accelerators that have been added in the survey this year is included.

Expedera has completed a $18m Series A funding round led by Dr. Sehat Sutardja and Weili Dai (founders of Marvell Technology Group) and other leading semiconductor industry investors. So far, the company has raises $27m and it will be using this new funding to speed product development and expand sales and marketing to meet the demand for its high performance and energy-efficient deep learning accelerator (DLA) IP. A growing number of semiconductor chip makers are adding AI (Artificial Intelligence) inference capabilities to applications, including smartphones, smart speakers, security cameras, PC/tablets, wearables, automotive, and edge servers. "We expect shipments of AI-enabled edge devices to grow from about 600m units in 2020 to 2bn units in 2025, representing 26% annual growth," said Linley Gwennap, Principal Analyst at The Linley Group. "Smartphones, a market where Expedera already has traction, represent about half of these units."

Airplanes and automobiles, databases and personal computers – all entities with ubiquitous form factors today, but that started out with diverging architectures. So it's not surprising that the shape of edge AI chip technology is similarly diversified. These are nascent days for AI chips. And with numerous designs in the market, there's unlikely to be a common architecture anytime soon. Today, established vendors and startup chip houses alike have jumped into the fray in a bid to complement or displace conventional microprocessors and controllers.

A staggering amount of money is pouring into data center AI chip companies at the moment. Data center AI chip companies are raising eye-watering amounts of money. In the last week, we've seen Groq announce a $300 million Series C round of funding, and SambaNova raise a staggering $676 million Series D. SambaNova is now valued at somewhere above $5 billion. They are not the only ones in this sector raising these huge amounts of money. Fellow data center AI chip companies Graphcore (raised $710 million, valued at $2.77 billion) and Cerebras (raised more than $475 million, valued at $2.4 billion) are hot on their heels as the sector continues to gain momentum.

Tucked in the Los Altos hills near the Stanford University campus, in a low-slung bunker of offices across from a coffee shop, is a lab overflowing with blinking machines putting circuits through their paces to test for speed, the silicon equivalent of a tool and die shop. Most chips you can balance on the tip of your finger, measuring just a centimeter on a side. Something very different is emerging here. Andrew Feldman, 50, chief executive of startup Cerebras Systems, holds up both hands, bracing between them a shining slab the size of a large mouse pad, an exquisite array of interconnecting lines etched in silicon that shines a deep amber under the dull fluorescent lights. At eight and a half inches on each side, it is the biggest computer chip the world has ever seen.

It may be a long time before you can own a truly self-driving car. But chipmakers are placing bets that you will. On Tuesday, the Japanese chipmaker Renesas, the second-largest provider of semiconductors for the automotive industry, said it will acquire San Jose based chipmaker Integrated Device Technology (IDT) for $6.7 billion, in part to prepare for autonomous vehicles. IDT has not historically provided chips for cars, but it does have sensor and wireless technologies that could help Renesas compete in the market for chips for autonomous vehicles. "Renesas and IDT have complementary technologies," says Objective Analysis analyst Jim Handy.

Everybody is taking a stab at designing artificial intelligence processors, or electronic chips that could become the brains of computers that act as if they were humans. The latest to tackle the task of designing AI chips is Vinod Dham, a former Intel executive known as the "father of the Pentium." He has teamed up with some younger chip designers to build RAP chips, or real AI processors. At AlphaICs, the team is creating a coprocessor chip that can do agent-based artificial intelligence. These RAP chips could one day be deployed in computing devices and autonomous cars to make decisions at lightning speeds, or in data centers on a massive scale.

Google uses AI for services like search, translation and face detection, but its AI chips, which it calls tensor processing units, run in data centers. Now AI chips are spreading to phones, PCs, cars and more. You've likely seen artificial intelligence technology spread into apps, devices and services, doing things like recognizing your friends' faces in photos and endowing smart speakers with human-sounding voices. Well, good news: The processor industry has noticed, too. That means we'll see a slew of new chips that should speed up AI tasks not just on your phone or laptop but also in your car or home security camera.

Google uses AI for services like search, translation and face detection, but its AI chips, which it calls tensor processing units, run in data centers. Now AI chips are spreading to phones, PCs, cars and more. You've likely seen artificial intelligence technology spread into apps, devices and services, doing things like recognizing your friends' faces in photos and endowing smart speakers with human-sounding voices. Well, good news: The processor industry has noticed, too. That means we'll see a slew of new chips that should speed up AI tasks not just on your phone or laptop but also in your car or home security camera.

Moore's Law, the principle that chips are supposed to get smaller and faster every few years, is faltering. But one company, Xilinx, thinks that's actually good news for a new type of flexible processors it expects to sell next year. You've heard of Intel, Apple and Samsung, some of the biggest chipmakers around. But you probably don't know Xilinx unless you're building things like high-end network equipment or self-driving cars. Xilinx's new chief executive, Victor Peng, hopes to change that.