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Ask HN: Any insider takes on Yann LeCun's push against current architectures?

385 points vessenes | 1 comments | 10 Mar 25 19:41 UTC | HN request time: 0.208s | 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.

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TrainedMonkey ◴[14 Mar 25 18:03 UTC] No.43365343[source]▶
This is a somewhat nihilistic take with an optimistic ending. I believe humans will never fix hallucinations. Amount of totally or partially untrue statements people make is significant. Especially in tech, it's rare for people to admit that they do not know something. And yet, despite all of that the progress keeps marching forward and maybe even accelerating.
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1. danielmarkbruce ◴[14 Mar 25 23:25 UTC] No.43368390[source]▶
Once one starts thinking of them as "concept models" rather than language models or fact models, "hallucinations" become something not to be so fixated on. We transform tokens into 12k+ length embeddings... right at the start. They stop being language immediately.

They aren't fact machines. They are concept machines.