图灵奖得主Sutton：合成数据是“大错误”
KI-Pioneer Sutton calls synthetic data a "big mistake" in the face of an infinitely complex world
Turing Award winner Richard Sutton calls synthetic data a "big mistake" for scaling large language models. The world is infinitely complex, and any simulation of it is "microscopic," with human expertise acting as a bottleneck that blocks real scaling. Sutton's alternative is agents that learn continually from their own experience instead of relying on frozen models.
图灵奖得主理查德·萨顿称，合成数据是扩展大型语言模型的一个“大错误”。世界是无限复杂的，任何对其的模拟都是“微观的”，人类专业知识成为阻碍真正扩展的瓶颈。萨顿提出的替代方案是让智能体从自身经验中持续学习，而不是依赖冻结的模型。
The article KI-Pioneer Sutton calls synthetic data a "big mistake" in the face of an infinitely complex world appeared first on The Decoder.
文章《面对无限复杂的世界，AI先驱萨顿称合成数据是“大错误”》首次出现在The Decoder上。
更进一步：量化金融体系
看懂新闻只是起点——沿量化金融路径，把它变成能交付的工程能力