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Ready for another description generated by chat? (It's so weirdly energized, yet lifeless. At least it's pretty accurate) Welcome to my latest project, where I set out on an unusual mission: to create the worst chess AI imaginable. In this video, I'll walk you through my journey of trying to design an AI that's exceptionally bad at chess, using neural evolution of augmenting topologies (NEAT) and bitboards. 🧩 The Puzzle: We start with a simple chess puzzle where your goal is to lose as White. Choices like rook a3, rook g3, or king b1 lead to mate in one. But there's a twist - the worst move isn't always obvious! 🤖 Worstfish Flaw: Discover the flaw I found in Worstfish, the chess bot that always plays the "worst move." This discovery inspired me to create my own AI. 🛠️ Building the AI: Before making an AI that's great at losing, I needed one that excels at winning. Using NEAT, I attempted to evolve an AI over generations. However, it wasn't as straightforward as I hoped. 🚀 Optimization Challenges: Learn about the various optimizations I implemented, including bitboards for efficient move calculations, move caching, multi-processing, and selective game play. Despite these improvements, training time was a significant hurdle. 🤯 Unexpected Outcomes: After optimizing, the AI still struggled, mainly pushing pawns. I tried numerous adjustments, including changing bitboards to an array of values and refining the fitness function, but results were underwhelming. 🧠 Mini-Max Algorithm: To give the AI better decision-making abilities, I incorporated a mini-max algorithm. However, the complexity of chess proved too much for my NEAT-based approach. 💡 Lessons Learned: Ultimately, NEAT wasn't suitable for this complex task. Although my AI couldn't master chess, it excelled at our original goal - losing games. It even managed to consistently draw against Worstfish. 🎬 Join the Journey: Watch as I navigate through the challenges of AI development, share the ups and downs, and finally, pivot towards more promising techniques for future projects. Don't forget to subscribe and hit the notification bell to stay updated on my latest videos and projects. Your support keeps me going! See you in the next one. Music: Summoning Salt - Chris Doerksen Zeta - Vincent Rubinetti We Shop Song - Lud & Schlatt's Music Emporium Cat - C418 https://github.com/Waz-ly/chess_ai_mk2.git