Keras作者批LLM：仅靠自回归采样无法解决物理世界任务
You can't solve real-world physical tasks through autoregressive sampling alone.…
推荐理由
直击当前具身智能痛点，Keras之父对纯自回归范式局限性的深刻反思，值得所有关注机器人落地与Agent架构的同学深思。
You can't solve real-world physical tasks through autoregressive sampling alone. The physical world is entirely unforgiving to hallucination or approximate pattern matching. If we want actual autonomous robotics we have to engineer causality and discrete reasoning back into the loop.
仅靠自回归采样无法解决现实世界的物理任务。物理世界对幻觉或近似模式匹配完全不容忍。如果我们想要真正的自主机器人，就必须将因果性和离散推理重新引入到系统中。
Biwei and the team at Aether AI is doing exactly the kind of foundational, non-consensus work the field actually needs right now.
Biwei 及其在 Aether AI 的团队正在开展该领域当前真正需要的、基础性的、非共识性工作。
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