DeepMind超大規模Transformer棋力驚人，挑戰AI規劃極限！
最近，DeepMind一篇關於超大規模 Transformer 在國際象棋領域應用的論文，引發了 AI 社區的廣泛討論。研究人員利用名爲 ChessBench 的全新數據集，訓練了多達2.7億參數的 Transformer 模型，探索其在棋類這種複雜規劃問題上的能力。ChessBench 數據集包含從 Lichess 平臺收集的1000萬局人類對弈棋譜，並使用頂級象棋引擎 Stockfish16對棋局進行了標註，提供了多達150億個數據點，包括每個棋局狀態的勝率、最佳走法以及所有合法走法的價值評估。研究人員使用監督學習方法，訓練 Transformer 模型預測給定棋
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