牛津研究团队发表论文称大模型无法真正“发明”新事物

作者认为，人类能够基于现有数据提出新理论，而大模型则只能反映过去。作者每天使用这些模型，发现新突破通常来自人类判断现有数据错误并做出新理论。

Can we have a moratorium on “influencers” using the phrase “just published” for papers published in 2024? Kanika @KanikaBK Oxford researchers just published a paper arguing LLMs cannot invent anything. Mathematically impossible. The reason is simple and brutal. A model trained to predict the next word can never believe something the existing data says is wrong. And every real breakthrough in history started with exactly that belief. In 1903 every prediction machine on Earth would have told the Wright Brothers that human flight was one to ten million years away. Nine weeks later they flew. Not because they had better data. Because they had a theory the data hadn't caught up to yet. That is the gap between AI and human thinking. LLMs mirror the past. Humans reason into a future that doesn't exist yet. Oxford just proved mathematically that those are two different things. I use these models every day. This matches what I see. The new stuff always comes from the human at the keyboard who decides the data is wrong. LLMs don't think. You do. 🔗 View Quoted Tweet📊 3 ⚡

本条情报归属 AITOP「论文」核心栏目，重点聚焦欧洲人工智能治理与技术生态。在跨区域产业观察坐标中，该动态直接关联「各国 AI 监管法案、合规治理与主权算力政策」研究主线，反映出当前技术演进与商业落地的最新风向。涉及核心实体与技术议题包括：LLMs、大模型、牛津、发明，读者可通过下方标签进入对应专题页查阅历史脉络与关联对比。

信源核验说明：本文原始线索采编自「Gary Marcus」（@GaryMarcus），经 AITOP 多维评分管线结构化提炼。