Liked this? Check out my post on "The 3 Ancient Joseki that Still Break Modern Neural Nets."
This wasn’t just another software update. It was the first time an AI beat a professional human player (Yoshio Ishida, 9p) at even odds using a neural network.
If you only know Lee Sedol vs. AlphaGo, you are missing the prequel—the scrappy, brilliant, and often-overlooked origin story of modern Go AI. Crazy Stone Deep Learning The First Edition
Before the deep learning explosion of 2016, there was . And in 2014, the world saw its true turning point: Crazy Stone Deep Learning, The First Edition .
Crazy Stone Deep Learning, The First Edition wasn't perfect. But it was the first time a machine stopped looking like a calculator and started looking like a Go player. Liked this
Let’s rewind and look at why this "first edition" was so crazy. Classic Go bots (Gnugo, early Crazy Stone) relied on Monte Carlo Tree Search (MCTS) . They played millions of random games in their head and guessed the best move based on statistics.
This worked well for amateurs but hit a wall at the professional level. Why? MCTS is terrible at intuition . It doesn't know a good shape from a bad one; it just knows brute-force probability. The "First Edition" of Crazy Stone with deep learning was a hybrid beast. The developer, Rémi Coulom (a French programmer), did something radical. If you only know Lee Sedol vs
Crazy Stone Deep Learning, The First Edition: The Moment the Machine Learned to "Feel" the Board
[Your Name] Category: Go & AI History
He kept the MCTS engine, but he added a as a "co-pilot."