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Top researchers are jumping ship from Big Tech firms like Meta and Google to launch startups and raise huge funding rounds in the process, as investors bet big on the commercial potential of early-stage AI labs.

Amid colossal spending on AI, many of these new startups are raising hundreds of millions within months of being founded.

On Monday, former Google DeepMind researcher David Silver announced he’d raised a record $1.1 billion seed round for his months-old startup Ineffable Intelligence. Tim Rocktäschel, another former DeepMind employee, is reportedly raising up to $1 billion for his new startup Recursive Superintelligence. Rocktäschel didn’t respond to a CNBC request for comment.

AMI Labs announced a $1 billion raise in March, months after its founder, Yann LeCun, said he was leaving his role as Meta’s AI chief. It’s developing AI systems that can learn from continuous real-world data.

In the past year, former staff at OpenAI, DeepMind, Anthropic and xAI also raised hundreds of millions from investors for months-old ventures, including AI labs Periodic Labs, Ricursive Intelligence and Humans&.

Many of these companies have themselves hired extensively from the founders’ former employers, and other AI giants, as investors have supplied them with the necessary funds to tempt top researchers from Big Tech.

The race for AI dominance among the biggest AI labs has created an opening for smaller, more nimble companies, Elise Stern, managing director at French VC Eurazeo, which backed AMI Labs, told CNBC.

“When you’re in a race, you narrow focus,” she added. “That creates a vacuum. Entire areas of research, like new architectures, agents, interpretability and vertical models, are being deprioritised, not because they don’t matter, but because they don’t win the immediate race.”

Investors are racing to pour funds into AI labs founded by top researchers previously working for leading tech companies.

In 2026, VCs have funnelled $18.8 billion into AI startups founded since the start of 2025, according to Dealroom. That’s on track to surpass the $27.9 billion picked up last year by companies launched since the start of 2024.

Founders who have worked at frontier labs have “unique” insight, said Eurazeo’s Stern.

“They know what works at scale, and they know exactly what is being left on the table internally,” she said. “That’s where the opportunity lies.”

Increasingly sharp focus on commercial goals — as major AI labs look to justify astronomical valuations — limits the freedom of top researchers, Alexander Joël-Carbonell, partner at HV Capital, which also invested in AMI Labs, told CNBC.

“Inside the large foundational labs, the pressure to deliver benchmark performance and maintain rapid release cycles leaves limited room for genuinely exploratory research, particularly outside the dominant LLM paradigm,” he added.

Finding gaps

Ricursive Intelligence, which picked up $335 million across two rounds in December and January after being founded in September, is building AI tools to help with chip design. Founders Anna Goldie and Azalia Mirhoseini both previously worked for Anthropic, as well as Google DeepMind, where they contributed to the AlphaChip project, which looked to automate chip design.

Goldie told CNBC that potential customers were more likely to consider a new company as a neutral partner rather than a competitor.

“For chipmakers to trust us with their most valuable IP, we have to be Switzerland, and that wouldn’t be possible if we were at Google,” she added.

The company has also turned to former colleagues. “We got the core AlphaChip team back together, and that involved hiring some of our old collaborators,” said Goldie. Other team members previously worked at Google, Anthropic, Nvidia, Apple and xAI, she added.

Periodic Labs, founded by former OpenAI and DeepMind staff, raised $300 million in September, months after launching. It’s looking to develop autonomous labs.

HV Capital’s Joël-Carbonell told CNBC that a growing number of AI researchers are questioning whether scaling the current large language model (LLM) approach further will be enough to reach the next level of AI capability.

AMI Labs, founded by former Meta AI chief LaCun, said that it was “the right moment because AI has made major progress in content generation, but still struggles with grounding, causality, and reliable behavior in real-world settings.”

Yann LeCun, chief AI scientist at Meta, speaks at the Viva Tech conference in Paris, June 13, 2023.

Chesnot | Getty Images News | Getty Images

“As AI moves beyond screens into industry, robotics, healthcare and other physical environments, those limitations become increasingly important,” a company spokesperson told CNBC.

Ineffable Intelligence will focus on reinforcement learning, which is when AI models learn from experience as opposed to human data — compared to many leading AI models that are trained on internet text — a source familiar with the company told CNBC.

It’s an approach also being used by San Francisco-based Humans&, which was launched in October by former employees of Anthropic and xAI and raised $480 million in January.

Google, Meta, Anthropic, and OpenAI did not respond to a request for comment.

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