The co-founders of the startup Recursive Intelligence appeared to be co-founders.
Anna Goldie, CEO, and Azalia Mirhoseini, CTO, are so well-known in the AI community that they were among the AI engineers who “got these weird emails from Zuckerberg making us crazy offers,” Goldie told TechCrunch with a laugh. (They did not accept the offers.) The pair worked together at Google Brain and were the first employees at Anthropic.
They made it all at Google by creating the Alpha Chip, an AI tool that could generate solid chip layouts in hours—a process that normally takes human designers a year or more. This tool helped design three generations of Google’s Tensor Processing Unit.
That pedigree explains why, just four months after launching Recursive, last month they announced a $300 million Series A round at a $4 billion valuation led by Lightspeed, just a few months after raising a $35 million seed round led by Sequoia.
Recursive builds AI tools that design chips, not the chips themselves. That’s what sets them apart from almost every other AI chip startup: they’re not Nvidia’s would-be competitors. In fact, Nvidia is an investor. The GPU giant, along with AMD, Intel and every other chip maker, are the startup’s target customers.
“We want to enable any chip, like a custom chip or a more traditional chip, any kind of chip, to be built in an automated and very accelerated way. We’re using AI to do that,” Mirhoseini told TechCrunch.
Their paths first crossed at Stanford, where Goldie earned her PhD, while Mirhoseini taught computer science classes. From then on, their careers went smoothly. “We started at Google Brain on the same day. We left Google Brain on the same day. We joined Anthropic on the same day. We left Anthropic on the same day. We rejoined Google on the same day and then left Google again on the same day. Then we co-founded this company on the same day,” Goldie recounted.
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During their time at Google, the colleagues were so close that they even worked out together and both enjoyed circuit training. Even Jeff Dean, a famous Google engineer who was their colleague, did not miss the pun. He nicknamed their project Alpha Chip “chip circuit training” – a play on their shared exercise routine. Internally, the pair were also nicknamed: A&A.
The Alpha Chip earned industry attention, but also caused controversy. In 2022, one of their colleagues at Google was fired, Wired reported, after years of trying to discredit A&A and their chip work, even though that work was used to make some of Google’s most important AI chips for business bets.
Their Alpha Chip project at Google Brain demonstrated a concept that would become Recursive – using artificial intelligence to dramatically speed up chip design.
Designing chips is hard
The problem is that computer chips have millions to billions of logic gate components integrated on their silicon wafer. Human designers can spend a year or more placing these components on a chip to ensure performance, good power utilization, and any other design needs. Digitally determining the location of such infinitesimal components with precision is, as might be expected, difficult.
Alpha Chip “could create a very high-quality layout in six hours. And the great thing about that approach was that it really learned from experience,” Goldie said.
The premise of their AI chip design work is the use of a “reward signal” that evaluates how good the design is. The agent then takes that assessment to “update the parameters of its deep neural network to improve itself,” Goldie said. After completing thousands of designs, the agent was really good. As it learned, it also got faster, the founders say.
The Recursive platform takes this concept further. The AI chip designer they’re building will “learn different chips,” Goldie said. So every chip he designs should help him become a better designer of every next chip.
The Recursive platform also uses LLM and handles everything from component placement to design verification. Any company that makes electronics and needs chips is their target customer.
If their platform proves as successful as it seems, Recursive could play a role in achieving the goal of artificial general intelligence (AGI). Their main vision is to design AI chips, which means that AI will essentially design its own computer brains.
“Chips are the fuel for AI,” Goldie said. “I think by making more powerful chips, that’s the best way to push that limit.”
Mirhoseini adds that the lengthy chip design process limits how quickly AI can progress. “We think we can also enable this rapid co-development of the models and the chips that essentially power them,” she said. Artificial intelligence can thus become smarter faster.
If the idea of AI designing its own brains at an ever-increasing rate brings visions of Skynet and the Terminator to mind, the founders point to a more positive, immediate and, they say, more likely benefit: hardware efficiency.
When AI Labs can design much more efficient chips (and eventually all the underlying hardware), their growth won’t need to consume as much of the world’s resources.
“We could design a computing architecture that is uniquely suited to this model and we could achieve almost a 10x performance improvement for the total cost of ownership,” Goldie said.
While the young startup won’t name its first customers, the founders say they’ve heard about every big chip you can imagine. Unsurprisingly, they’ve also chosen their first development partners.