Why Can't AI Make Its Own Discoveries? — With Yann LeCun
Alex Kantrowitz2 HN recommenders · recommended in 2 months, 2025–2026
podcast · general · 2025–2026 on HN
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.
Pointed to as LeCun's argument for the limits of LLMs and the need for world models.
Up next
6 mo on HNFunctional architecture - The pits of success - Mark Seemann
NDC Conferences
5 HN recommender · 2018–2025
10 mo on HNTransformers, the tech behind LLMs | Deep Learning Chapter 5
3Blue1Brown
13 HN recommender · 2024–2026
8 mo on HNDeep Dive into LLMs like ChatGPT
Andrej Karpathy
10 HN recommender · 2025–2026
8 mo on HNLet's build GPT: from scratch, in code, spelled out.
Andrej Karpathy
14 HN recommender · 2023–2025
8 mo on HNA Hackers' Guide to Language Models
Jeremy Howard
8 HN recommender · 2023–2024
6 mo on HN[1hr Talk] Intro to Large Language Models
Andrej Karpathy
9 HN recommender · 2023–2026
4 mo on HNSparks of AGI: early experiments with GPT-4
Sebastien Bubeck
7 HN recommender · 2023–2026
5 mo on HNLet's build the GPT Tokenizer
Andrej Karpathy
5 HN recommender · 2024–2025
4 mo on HNAttention in transformers, step-by-step | Deep Learning Chapter 6
3Blue1Brown
5 HN recommender · 2024–2026
4 mo on HNThe A.I. Dilemma - March 9, 2023
Center for Humane Technology
11 HN recommender · 2023–2024
4 mo on HNLSTM is dead. Long Live Transformers!
Seattle Applied Deep Learning
4 HN recommender · 2020–2023
4 mo on HNAttention Is All You Need
Yannic Kilcher
4 HN recommender · 2020–2025
3 comments from Hacker News
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
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
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 )