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385 points vessenes | 1 comments | | HN request time: 3.854s | source

So, Lecun has been quite public saying that he believes LLMs will never fix hallucinations because, essentially, the token choice method at each step leads to runaway errors -- these can't be damped mathematically.

In exchange, he offers the idea that we should have something that is an 'energy minimization' architecture; as I understand it, this would have a concept of the 'energy' of an entire response, and training would try and minimize that.

Which is to say, I don't fully understand this. That said, I'm curious to hear what ML researchers think about Lecun's take, and if there's any engineering done around it. I can't find much after the release of ijepa from his group.

1. zmmmmm ◴[] No.43369250[source]
So much of our fundamental scientific progress has been made by people who were considered crazy and their ideas delusional. Even mundane software engineering is done with layers of code review and automated tests because even the best engineers are still pretty bad at it. At a larger level, humanity itself seems to largely operate more like an ensemble method where many people in parallel solve problems and we empirically find who was "hallucinating".

Which is just to say, it feels to me like there's a danger that the stochastic nature of outputs is fundamental to true creative intelligence and all attempts to stamp it out will result in lower accuracy overall. Rather we should be treating it more like we do actual humans and expect errors and put layers of process around things where it matters to make them safe.