The DeepMind trio who built a poker AI, are now making money for quant hedge funds

A trio of former DeepMind researchers, who developed an AI capable of defeating humans in poker, have now turned their innovative technology towards stock trading, with promising results. Their company, EquiLibre Technologies, based in Prague, has recently achieved a valuation of $500 million after securing a Series A funding round, the details of which remain undisclosed. This funding round, led by Creandum, was noted by vice president Cameron Sellers as the largest single investment the firm has ever made into a single company. The link between poker and stock trading lies in the suitability of both fields for reinforcement learning, a method where AI models learn through rewards. Martin Schmid, the CEO of EquiLibre, emphasized the simplicity of scoring in trading, stating, "The nice thing about trading and markets is that the scoring is super simple: how much money did the agent make?" This is not merely theoretical; in collaboration with Tower Research Capital, EquiLibre's algorithms are actively involved in trading substantial volumes daily across the S&P 500 and NASDAQ. Since launching on crypto markets in 2025, the startup claims its trading agents have maintained an impressive track record, finishing each month positively without any losses. By integrating their AI into quantitative hedge funds, EquiLibre is tapping into a highly automated sector, where enhancements can rapidly lead to significant financial gains. Sellers remarked on the immense potential within the financial trading market, highlighting that successful quant funds have historically accrued profits that dwarf many venture-backed successes. Despite the financial potential, Schmid and his co-founders—CTO Rudolf Kadlec and CSO Matej Moravcik—are not primarily motivated by profits. Schmid shared, "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." EquiLibre's founding team previously worked together as PhD students at DeepMind's international AI research office in Edmonton, Canada, where they created DeepStack, the first AI to beat professional players in no-limit Texas hold'em poker. Their decision to relocate back to Czechia was deliberate, as they sought to build a team of familiar colleagues. With a current workforce of 25, the location has proven advantageous, allowing them to retain talent more easily compared to tech hubs like San Francisco. EquiLibre plans to expand its computing infrastructure, aiming to establish one of the largest compute clusters in Central and Eastern Europe. Having previously raised funds from various investors, including a $10 million seed round led by Blossom Capital, the recent Series A funding marks a significant leap in valuation for the startup. Schmid noted the increased acceptance of reinforcement learning in trading, stating, "When we started, people were skeptical. But now RL is the standard. We believe we are ahead." Nonetheless, competition remains fierce, with trading giants like Jane Street already employing reinforcement learning techniques in their operations. As EquiLibre seeks to carve out its niche in the trading AI landscape, Schmid remains optimistic, asserting, "This is not a winner-takes-all market. There might be no losers."