@ericjang11: For the last few months I've been working on a from-scratch implementation of AlphaGo, a 2016 AI breakthrough that insp…
Summary
Eric Jang releases AutoGo, a from-scratch tutorial for implementing AlphaGo, including code and a playable bot, demonstrating that frontier capabilities can now be replicated affordably.
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For the last few months I’ve been working on a from-scratch implementation of AlphaGo, a 2016 AI breakthrough that inspired me to get into deep learning. My casual understanding of AlphaGo was “search-augmented deep neural networks trained with self-play”, but I wanted to go deeper and understand it by creating it. Frontier deep learning research has always been expensive, but any given capability gets cheaper very quickly. In 2026, you no longer need DeepMind’s resources to train a strong Go AI - you can vibe code all of it yourself for just a few thousand dollars of rented compute. It was a huge honor to be invited to teach this with @dwarkesh_sp on @dwarkeshpodcast I am an AlphaGo & Go apprentice, not a master, so all factual errors in the podcast are mine. Web version of tutorial: https://evjang.com/2026/04/28/autogo.html… Code: https://github.com/ericjang/autogo Play the go bot here: https://autogo.evjang.com
AutoGo: a Tutorial
Source: https://evjang.com/2026/04/28/autogo.html AutoGo
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The tutorial uses a wide canvas — it needs the horizontal room.
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