Why Can't AI Make Its Own Discoveries? — With Yann LeCun
Why Hacker News recommends it
Pointed to as LeCun's argument for the limits of LLMs and the need for world models.
What it is
Yann LeCun on the Big Technology Podcast discusses why current AI models cannot make discoveries despite their knowledge. He argues systems need abstract world models and also covers limits of AI research, investor expectations, and open source after DeepSeek.
Recommended by 2 HN commenters across 2 different months, 2025 to 2026.
What Hacker News said
Recommends Xunjin · 2026-03 · on “Why AI systems don't learn – On autonomous learning from cognitive science”
In this podcast episode[0] he does talk about this kind of model and how it "learns about physics" through experience instead of just ingesting theorical material. It's quite eye opening. 0. [this video]
Recommends qsera · 2026-04 · on “I used AI. It worked. I hated it”
This is not an appeal to authority, but this video probably contains the answers to your questions if you are open minded about it [this video]
Cites mentalgear · 2025-03 · on “Tracing the thoughts of a large language model”
What? The "article" is from anthropic, so I think they would know what they write about. Also, RL is an additional training process that does not negate that GPT / transformers are left-right autoencoders that are effectively next token predictors. [Why Can't AI Make Its Own Discoveries? — With Yann LeCun] ( [this video] )