Let me introduce my favorite company in the RL series, EquiLibre. This company is most like Deepseek. They are a cutting-edge AI Lab, not positioned as a quantitative trading company, but quantitative trading is their first application scenario. Their advisor is still RL founder Rich Sutton. At the same time, SBF's investment vision and network in the technology startup community are top-notch. This company was invested by SBF in the early days, and its equity was sold at a low price after the FTX crash. Now, the company's valuation exceeds $500 million. EquiLibre: Quantitative Trading by DeepMind Poker AI Team The three founders are Martin Schmid (CEO), Mat ě j Morav č í k (CSO), and Rudolf Kadlec (CTO). Schmid and Morav č í k are authors of DeepStack: Around 2017, this system became the first AI to defeat professional players in unlimited Texas Hold'em. DeepStack related technology was later acquired by Google, and the three of them joined DeepMind's research office in Edmonton, Canada, to work on reinforcement learning and game strategies; Kadlec also works with them at DeepMind. The advisors include Rich Sutton, a pioneer in reinforcement learning and winner of the 2024 Turing Award. They are expected to return to the Czech Republic at the end of 2021 to establish EquiLibre, with a positioning more like 'laboratory first, financial company second'. The core approach is to train trading agents using game theory and reinforcement learning: first learn by trial and error on historical and real-time market data, and then place orders autonomously. Early verification on cryptocurrencies, later shifted to high liquidity markets such as the US stock market. Collaborating with Tower Research Capital, a quantitative firm based in New York, the algorithm has achieved monthly trading volumes in the billions of dollars on the S&P 500 and Nasdaq related markets, and has stated that there have been no loss making months since its launch. The team consists of approximately 25 people, working in Prague without remote access; A large part of the financing is used for computing power, claiming to have built one of the largest AI training clusters in Central and Eastern Europe. Company financing situation: 2022 pre sold: Approximately $6 million, with investors including Credo Ventures, Miton, and RockawayX, known as the largest pre sold in Czech history at the time. Afterwards, the seed was $10 million, led by Blossom Capital in London, with a valuation of approximately $140 million (approximately € 123 million). Series A at the beginning of 2026: Led by Creandum from Sweden (the fund claims this is one of its largest single investments), with a post investment valuation of approximately $500 million (approximately € 438 million, equivalent to approximately CZK 10.6 billion). Richard Sutton also participated in the list of investors. These types of companies are all closed source, with limited publicly available technical information and more focused on RL games against Texas, https://arxiv.org/abs/1701.01724 The big difference between Texas Hold'em and Go is that they have imperfect information, where both players see the same board. Given the rules and current situation, legal actions and where they will go in the future are all public knowledge. In theory, there exists a definite optimal approach (or several equivalent approaches). Methods like AlphaGo can harvest a situation into a state and use a search value network to estimate the probability of winning from this situation. Texas is not. You only see your own trump cards and public cards, not your opponent's trump cards, and your opponent cannot see yours either. The same common deck corresponds to a possible hand combination of the entire clan behind it. Your bet is both taking the expected value and conveying or hiding information. Opponents will update their beliefs about your hand based on your actions, and you will also take advantage of this in turn. So there is no such thing as a unique strategy that is unrelated to private information as' this situation should be bet '. There is only a mixed strategy that needs to be executed according to the distribution of the hand: place more bets on strong cards, re bet on some medium cards, and discard most weak cards, otherwise they will be exploited by card reading. And this is exactly similar to trading. Source: Interview with the CEO of EquiLibre https://mp.weixin. (qq.com)/s/oITAXph69anM54TERgbhpg In addition, Prague in the Czech Republic is a beautiful small town, and their official website has relevant introductions https://equilibre.ai/