[xuancanh]

Meta did exactly that, kept him but reduced his scope. Did the broader research community benefit from his research? Absolutely. But did Meta achieve a good outcome? Probably not.

If you follow LeCun on social media, you can see that the way FAIR’s results are assessed is very narrow-minded and still follows the academic mindset. He mentioned that his research is evaluated by: "Research evaluation is a difficult task because the product impact may occur years (sometimes decades) after the work. For that reason, evaluation must often rely on the collective opinion of the research community through proxies such as publications, citations, invited talks, awards, etc."

But as an industry researcher, he should know how his research fits with the company vision and be able to assess that easily. If the company's vision is to be the leader in AI, then as of now, he seems to have failed that objective, even though he has been at Meta for more than 10 years.

[nsonha]

Also he always sounds like "I know this will not work". Dude are you a researcher? You're supposed to experiment and follow the results. That's what separates you from oracles and freaking philosophers or whatever.

[lukan]

Philosophers are usually more aware of their not knowing than you seem to give them credit for. (And oracles are famously vague, too).

[teleforce]

Do you know that all formally trained researchers have Doctor of Philosophy or PhD to their name? [1]

[1] Doctor of Philosophy:

https://en.wikipedia.org/wiki/Doctor_of_Philosophy

[anotherd1p]

If academia is in question, then so are their titles. When I see "PhD", I read "we decided that he was at least good enough for the cause" PhD, or PhD (he fulfilled the criteria).

[yawnxyz]

he probably predicted the asymptote everyone is approaching right now

[brazukadev]

So did I after trying llama/Meta AI

[uoaei]

He's speaking to the entire feedforward Transformer-based paradigm. He sees little point in continuing to try to squeeze more blood out of that stone and instead move on to more appropriate ways to model ontologies per se rather than the crude-for-what-we-use-them-for embedding-based methods that are popular today.

I really resonate with his view due to my background in physics and information theory. I for one welcome his new experimentation in other realms while so many still hack away at their LLMs in pursuit of SOTA benchmarks.

[fhd2]

If the LLM hype doesn't cool down fast, we're probably looking at another AI winter. Appears to me like he's just trying to ensure he'll have funding for chasing the global maximum going forward.

[re-thc]

> If the LLM hype doesn't cool down fast, we're probably looking at another AI winter.

Is the real bubble ignorance? Maybe you'll cool down but the rest of the world? There will just be more DeepSeek and more advances until the US loses its standing.

[uoaei]

How is it a foregone conclusion that squeezing the stone will continue to produce blood?