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765 points MindBreaker2605 | 1 comments | | HN request time: 0.217s | source
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sebmellen ◴[] No.45897467[source]
Making LeCun report to Wang was the most boneheaded move imaginable. But… I suppose Zuckerberg knows what he wants, which is AI slopware and not truly groundbreaking foundation models.
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gnaman ◴[] No.45897498[source]
He is also not very interested in LLMs, and that seems to be Zuck's top priority.
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tinco ◴[] No.45897523[source]
Yeah I think LeCun is underestimating the impact that LLM's and Diffusion models are going to have, even considering the huge impact they're already having. That's no problem as I'm sure whatever LeCun is working on is going to be amazing as well, but an enterprise like Facebook can't have their top researcher work on risky things when there's surefire paths to success still available.
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jll29 ◴[] No.45897673[source]
I politely disagree - it is exactly an industry researcher's purpose to do the risky things that may not work, simply because the rest of the corporation cannot take such risks but must walk on more well-trodden paths.

Corporate R&D teams are there to absorb risk, innovate, disrupt, create new fields, not for doing small incremental improvements. "If we know it works, it's not research." (Albert Einstein)

I also agree with LeCun that LLMs in their current form - are a dead end. Note that this does not mean that I think we have already exploited LLMs to the limit, we are still at the beginning. We also need to create an ecosystem in which they can operate well: for instance, to combine LLMs with Web agents better we need a scalable "C2B2C" (customer delegated to business to business) micropayment infrastructure, because as these systems have already begun talking to each other, in the longer run nobody would offer their APIs for free.

I work on spatial/geographic models, inter alia, which by coincident is one of the direction mentioned in the LeCun article. I do not know what his reasoning is, but mine was/is: LMs are language models, and should (only) be used as such. We need other models - in particular a knowledge model (KM/KB) to cleanly separate knowledge from text generation - it looks to me right now that only that will solve hallucination.

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siva7 ◴[] No.45897749[source]
> it is exactly a researcher's purpose to do the risky things that may not work

Maybe at university, but not at a trillion dollar company. That job as chief scientist is leading risky things that will work to please the shareholders.

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1. rsynnott ◴[] No.45898264[source]
“Risky things that will work” - contradiction in terms. If companies only did things they knew would work, we probably still wouldn’t have microchips.

Also, like… it’s Facebook. It has a history of ploughing billions into complete nonsense (see metaverse). It is clearly not particularly risk averse.