Yann LeCun 用具体数字对比，讲清了 LLM 为什么看起来聪明却不懂物理常识。想理解当前 AI 天花板的人可以看看。
Yann LeCun 在 Bloomberg 采访中指出，LLM 预训练于约 20 万亿单词（30 万亿 token），数据量约 10^14 字节，仅相当于一个 4 岁孩子通过视觉在 4 年内获取的数据量。但文本需要 40 万年才能读完，而孩子通过视觉、触觉等感官获得密集反馈。LeCun 引用 Moravec's paradox，认为理解物理世界（如玻璃杯的易碎感）远比生成流畅文本困难。
amazing how much shit @ylecun used to give me for saying basically this pathological that he won’t...
amazing how much shit @ylecun used to give me for saying basically this pathological that he won’t acknowledge it Rohan Paul @rohanpaul_ai During a Bloomberg interview, Yann LeCun ( @ylecun ) explains why LLMs are limited in terms of real-world intelligence during a Bloomberg interview. "Language is a very approximate, reduced, quantized, and simplified description of the world, and LLMs can only deal with discrete sequences of symbols. The world is much more complicated than language. The biggest LLMs are pre-trained on the totality of all the publicly available text on the internet. That’s about 20 trillion words, or 30 trillion tokens. A token is about 3 bytes. So total 10¹⁴ bytes of text. This is the amount of data a four-year-old has seen through vision during four years. Now, the text, though, would take 400,000 years to read? So, there is enormously more data from sensory input, like vision, touch, and everything else, than there could ever be through language." A child does not need 400,000 years of reading to understand cups, doors, balance, faces, falls, or heat, because the body is already collecting dense feedback from vision, touch, motion, and consequence. Text strips most of that away. It turns a living scene into symbols, then asks the model to infer the missing world from traces left by people describing it. That is why an LLM can sound fluent about physics and still have no native sense of how fragile glass feels in a hand. Moravec’s paradox names this reversal: the things humans find intellectual can be easier for machines than the things toddlers do without applause. The hard part is not producing an answer, but building a model of the world that survives contact with weight, friction, surprise, and failure. ---- Link to the full video on Bloomberg's site. Link in comment. Your browser does not support the video tag. 🔗 View on Twitter 🔗 View Quoted Tweet 💬 2 🔄 1 ❤️ 14 👀 1440 📊 3 ⚡
- IT之家07-08 13:33原文