When AI merged gameplay and language, everything changed...Sponsored by Brilliant | Use https://brilliant.org/artoftheproblem for 30-day free trial and 20% discount
My goal here is to introduce model based learning and show how language understanding merged with gameplay AI strategies recently. From early chess engines to modern language models (
OpenAI o1, Google Gemini etc.). We examine key breakthroughs in game-playing AI—TD-Gammon, AlphaGo, and MuZero—and their contribution to current large language model architectures. Special focus on the convergence of Monte Carlo Tree Search (MCTS) with neural networks, and how these techniques transformed into today's chain-of-thought reasoning. Deepseek Deep Seek SUPPORT this work: https://www.patreon.com/artoftheproblem
Timestamps:
00:00 intro
01:00 definition of reasoning
03:57 intuition
06:35 MCTS
07:40 AlphaGO
09:37 World Models
10:36 MuZero
12:45 Chain/Tree of Thought
14:03 RL on Reasoning
15:41 ARC AGI Test