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Cover image for $10,000,000 was sitting at the
$10,000,000 was sitting at the top of the 2026 WSOP Main Event. That number is one of the reasons I became interested in building this. Poker isn't just cards on a screen. At the highest level, millions of dollars can depend on thousands of individual decisions. So I'm building something around a question that I find technically fascinating: Can software understand what is happening on a poker table from visual data? That's what I'm working on with my Poker Vision project. The system is being designed to recognize and structure information such as: → 🃏 Hole cards → 🎴 Board cards → 👤 Player positions → 💰 Betting actions → 🔎 OCR information → 📍 Table coordinates → 🧠 Game-state changes Then the challenge becomes turning all of that raw visual information into reliable structured data that another part of the application can understand. And that's where the engineering gets serious. A single recognition mistake can completely change the state of the game. So I'm not interested in building something that simply looks intelligent. I want to build something that can: Detect → Interpret → Validate → Test → Learn from errors → Improve. One important boundary: I'm building this as a research/analysis and development project, not a real-time system that tells someone what action to take during live-money play. Major poker platforms prohibit real-time assistance that influences decisions during play. PokerStars (https://www.pokerstars.com/poker/room/prohibited/?utm_source=chatgpt.com) The bigger idea is what excites me: Computer vision + AI + poker data + software engineering. When the stakes can reach millions, even a small technical problem becomes an interesting engineering problem. And that's exactly the kind of problem I enjoy building. 🔥 If you were building this system, what would you tackle first: card recognition, player tracking, OCR, or game-state detection?
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