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GPT-2 and Chess

Shawn Presser has released an intringuing chess engine based on deep learning-based language model (GPT-2). The model was trained on the Kingbase dataset (3.5 million chess games in PGN notation) in 24 hours using 146 TPUs (ouch!). The engine is purely based on text prediction with no concept of chess. Though GPT-2 has already delivered promising/bluffing results for text generation, one can be skeptical and wonder whether it does work for chess.



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GPT-2 and Chess

https://blog.mathieuacher.com/GTP2AndChess

Shawn Presser has released an intringuing chess engine based on deep learning-based language model (GPT-2). The model was trained on the Kingbase dataset (3.5 million chess games in PGN notation) in 24 hours using 146 TPUs (ouch!). The engine is purely based on text prediction with no concept of chess. Though GPT-2 has already delivered promising/bluffing results for text generation, one can be skeptical and wonder whether it does work for chess.



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https://blog.mathieuacher.com/GTP2AndChess

GPT-2 and Chess

Shawn Presser has released an intringuing chess engine based on deep learning-based language model (GPT-2). The model was trained on the Kingbase dataset (3.5 million chess games in PGN notation) in 24 hours using 146 TPUs (ouch!). The engine is purely based on text prediction with no concept of chess. Though GPT-2 has already delivered promising/bluffing results for text generation, one can be skeptical and wonder whether it does work for chess.

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      GPT-2 and Chess – Mathieu Acher – Professor in Computer Science
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      Shawn Presser has released an intringuing chess engine based on deep learning-based language model (GPT-2). The model was trained on the Kingbase dataset (3.5 million chess games in PGN notation) in 24 hours using 146 TPUs (ouch!). The engine is purely based on text prediction with no concept of chess. Though GPT-2 has already delivered promising/bluffing results for text generation, one can be skeptical and wonder whether it does work for chess.
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