Former DeepMind Researchers Turn Poker AI to Stock Trading Success

Three former DeepMind researchers who created an AI that beat humans at poker have now applied the same technology to trading stocks — and the bet appears to be paying off. Their Prague-based AI lab, EquiLibre Technologies, is now valued at $500 million after raising an undisclosed-sum Series A. The round was led by Creandum, and, although the VC also declined to disclose the size of the round, vice president Cameron Sellers confirmed that it was the largest single investment the firm “has ever made in one go into a company,” he told TechCrunch.

The common denominator between poker and Wall Street is that they are well suited for reinforcement learning, an AI training technique where self-learning models are incentivized by rewards. According to Martin Schmid, EquiLibre CEO, “The nice thing about trading and markets is that the scoring is super simple: how much money did the agent make?” This isn’t just game money. In partnership with quant firm Tower Research Capital, EquiLibre’s algorithms have been trading billions in daily volume across the S&P 500 and Nasdaq.

The startup claims its agents have been doing well since their rollout on crypto markets in 2025, and now on stock exchanges, with “a perfect record of zero negative months since inception,” meaning they have finished each month with their investments up overall. By applying its AI to quant hedge funds, the startup is in a field where automation is commonplace and, if successful, improvements can quickly turn into cash. That made the startup appealing to Creandum, Sellers said.

“The potential total addressable market of trading in the financial markets is one of the biggest on earth, and there are countless funds over the years that have generated quantums of profit that make most venture-backed successes look small,” Sellers said. But he noted that EquiLibre explicitly defines itself as “a lab first, not a finance firm.” Schmid and his two founders — CTO Rudolf Kadlec and CSO Matej Moravcik — don’t have a background in finance, and it is not what drives them, he told TechCrunch. “I’m not doing this because I’m excited about making markets efficient.

I’m doing this because we are all excited about building new things that have never been built before, and this is a lot of fun to build,” Schmid said. The prospect of frontier AI by DeepMind alumni is an area of hot pursuit by VCs as well. Another recent such example is Ineffable Intelligence, which recently raised $1.1 billion.

Most of these are based in the U.K., but there are notable exceptions, including EquiLibre. In the case of EquiLibre’s founding trio, they were visiting PhD students at the Google-owned company’s first international AI research office in Edmonton, Alberta, Canada (which Alphabet shut down in 2023.) While there, they built DeepStack, the first AI program to defeat pro players at no-limit poker, also known as Texas hold ’em. They also worked with professors who are now part of the startup’s high-profile advisory board — including Rich Sutton, who went on to receive the Turing award in 2024 for his work on reinforcement learning.