Yann LeCun says strong code-generation systems go beyond plain autoregressive LLMs
ylecun · x · 2026-08-04
Yann LeCun says good code-generation systems are not just autoregressive LLMs
In a reply to @gabriberton, Yann LeCun clarified that his earlier point was specifically about pure autoregressive token prediction, which is what plain LLMs do.
He added that good code generation systems are not pure LLMs and are not limited to simple autoregressive token prediction.
The post is brief, but it restates LeCun’s broader position: code-generation tooling can involve more than just next-token prediction, and that distinction matters when comparing LLMs with practical coding systems.
Related event: LeCun: Strong Code Generation Needs More Than Autoregressive LLMs(2 posts)→
More from AGI Musings
- A sci-fi image about machinery replacing mystery but not fear — piotrbinkowski · 2026-08-04
- Opinion warns AI could trigger bankruptcies and bank failures — charliepscott · 2026-08-04
- A simple prefix-and-sample test reveals bias in video models — Kangwook_Lee · 2026-08-04
- Models keep ending with “shall we continue?” 99,111 times in one archive — henkvaness · 2026-08-04
- As AI makes intelligence cheap, spotting foolishness becomes the premium skill — MazMansoor · 2026-08-04
- Polling suggests voters like AI but dislike data centers, while OpenAI stays net positive — zacharynado · 2026-08-04