Gary Marcus：AI需要可审计的推理过程
Gary Marcus刚离开DeepMind，他解释为什么当前AI缺乏真正推理能力，并提出了改进方向。
Gary Marcus在《科技评论》撰文指出，当前最先进的AI系统仍缺乏基本推理能力。他提到AlphaGo的Move37展示了真正的推理过程，而LLMs仅能生成更长思维链，缺乏可检查的知识记录和证据支持。Marcus认为需要借鉴AlphaGo架构，开发具有可审计推理过程的新AI系统。
💯💯💯: “If AI is going to produce trustworthy and genuinely novel insights in science, medicine and beyond, we need systems whose conclusions arise from an auditable process of evidence, inference and belief revision.” It is madness to believe otherwise. Thore Graepel @ThoreG Ten years ago, AlphaGo’s Move 37 shocked the world. It wasn’t intuition alone that produced it. AlphaGo could search possible futures, test its instincts and reason about what would happen next. In a new piece for @techreview , I argue that today’s most advanced AI systems are still missing something fundamental. LLMs are remarkably capable, but generating longer chains of thought is not the same as genuine reasoning. They typically have no explicit, inspectable record of what they know, what remains uncertain, what evidence supports a conclusion or whether genuine progress has been made. This is why I recently left @GoogleDeepMind . I believe we need a fresh approach to machine reasoning, drawing on some of the architectural lessons from AlphaGo. If AI is going to produce trustworthy and genuinely novel insights in science, medicine and beyond, we need systems whose conclusions arise from an auditable process of evidence, inference and belief revision. 🔗 View Quoted Tweet 💬 21 🔄 66 ❤️ 346 👀 25131 📊 63 ⚡