DeepMind超大规模Transformer棋力惊人，挑战AI规划极限！
最近，DeepMind一篇关于超大规模 Transformer 在国际象棋领域应用的论文，引发了 AI 社区的广泛讨论。研究人员利用名为 ChessBench 的全新数据集，训练了多达2.7亿参数的 Transformer 模型，探索其在棋类这种复杂规划问题上的能力。ChessBench 数据集包含从 Lichess 平台收集的1000万局人类对弈棋谱，并使用顶级象棋引擎 Stockfish16对棋局进行了标注，提供了多达150亿个数据点，包括每个棋局状态的胜率、最佳走法以及所有合法走法的价值评估。研究人员使用监督学习方法，训练 Transformer 模型预测给定棋
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