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Yann LeCun raises $1B to build AI that understands the physical world

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Re: Yann LeCun raises $1B to build AI that understands the physical world

#191

Post by GorbachevyChase »

stein1946 wrote: post #95
Oras wrote: post #58

> But this is not an applied AI company. There is absolutely no doubt about Yann's impact on AI/ML, but he had access to many more resources in Meta, and we didn't see anything. It could be a management issue, though, and I sincerely wish we will see more competition, but from what I quoted above, it does not seem like it. Understanding world through videos (mentioned in the article), is just what video models have a…

> There is absolutely no doubt about Yann's impact on AI/ML, but he had access to many more resources in Meta, and we didn't see anything. That's true for 99% of the scientists, but dismissing their opinion based on them not having done world shattering / ground breaking research is probably not the way to go. > I sincerely wish we will see more competition I really wish we don't, science isn't markets. > Understandi…

Do not keep bad results in context. You have to purge them to prevent them from effecting the next output. LLMs deceptively capable, but they don’t respond like a person. You can’t count on implicit context. You can’t count on parts of the implicit context having more weight than others.

Re: Yann LeCun raises $1B to build AI that understands the physical world

#192

Post by dheera »

jsnell wrote: post #117
ZeroCool2u wrote: post #32

Regardless of your opinion of Yann or his views on auto regressive models being "sufficient" for what most would describe as AGI or ASI, this is probably a good thing for Europe. We need more well capitalized labs that aren't US or China centric and while I do like Mistral, they just haven't been keeping up on the frontier of model performance and seem like they've sort of pivoted into being integration specialists a…

I don't think it's "regardless", your opinion on LeCun being right should be highly correlated to your opinion on whether this is good for Europe. If you think that LLMs are sufficient and RSI is imminent (<1 year), this is horrible for Europe. It is a distracting boondoggle exactly at the wrong time.

Just because you raise 1 billion dollars to do X doesn't mean you can't pivot and do Y if it is in the best interest of your mission.

I won't comment on Yann LeCun or his current technical strategy, but if you can avoid sunk cost fallacy and pivot nimbly I don't think it is bad for Europe at all. It is "1 billion dollars for an AI research lab", not "1 billion dollars to do X".

Re: Yann LeCun raises $1B to build AI that understands the physical world

#193

Post by [deleted] »

ZeroCool2u wrote: post #32

Regardless of your opinion of Yann or his views on auto regressive models being "sufficient" for what most would describe as AGI or ASI, this is probably a good thing for Europe. We need more well capitalized labs that aren't US or China centric and while I do like Mistral, they just haven't been keeping up on the frontier of model performance and seem like they've sort of pivoted into being integration specialists a…

[deleted]

Re: Yann LeCun raises $1B to build AI that understands the physical world

#194

Post by andreyk »

Oras wrote: post #58

> But this is not an applied AI company. There is absolutely no doubt about Yann's impact on AI/ML, but he had access to many more resources in Meta, and we didn't see anything. It could be a management issue, though, and I sincerely wish we will see more competition, but from what I quoted above, it does not seem like it. Understanding world through videos (mentioned in the article), is just what video models have a…

"and we didn't see anything" is not justified at all.

Meta absolutely has (or at least had) a word class industry AI lab and has published a ton of great work and open source models (granted their LLM open source stuff failed to keep up with chinese models in 2024/2025 ; their other open source stuff for thins like segmentation don't get enough credit though). Yann's main role was Chief AI Scientist, not any sort of product role, and as far as I can tell he did a great job building up and leading a research group within Meta.

He deserved a lot of credit for pushing Meta to very open to publishing research and open sourcing models trained on large scale data.

Just as one example, Meta (together with NYU) just published "Beyond Language Modeling: An Exploration of Multimodal Pretraining" (https://arxiv.org/pdf/2603.03276) which has a ton of large-experiment backed insights.

Yann did seem to end up with a bit of an inflated ego, but I still consider him a great research lead. Context: I did a PhD focused on AI, and Meta's group had a similar pedigree as Google AI/Deepmind as far as places to go do an internship or go to after graduation.

Re: Yann LeCun raises $1B to build AI that understands the physical world

#195

Post by devonkelley »

jsnell wrote: post #117
ZeroCool2u wrote: post #32

Regardless of your opinion of Yann or his views on auto regressive models being "sufficient" for what most would describe as AGI or ASI, this is probably a good thing for Europe. We need more well capitalized labs that aren't US or China centric and while I do like Mistral, they just haven't been keeping up on the frontier of model performance and seem like they've sort of pivoted into being integration specialists a…

I don't think it's "regardless", your opinion on LeCun being right should be highly correlated to your opinion on whether this is good for Europe. If you think that LLMs are sufficient and RSI is imminent (<1 year), this is horrible for Europe. It is a distracting boondoggle exactly at the wrong time.

[flagged]

Re: Yann LeCun raises $1B to build AI that understands the physical world

#197

Post by LarsDu88 »

There's been a few very interesting JEPA publications from LeCun recently, particularly the leJEPA paper which claims to simplify a lot of training headaches for that class of models.

JEPAs also strike me as being a bit more akin to human intelligence, where for example, most children are very capable of locomotion and making basic drawings, but unable to make pixel level reconstructions of mental images (!!).

One thing I want to point out is that very LeCunn type techniques demonstrating label free training such as JEAs like DINO and JEPAs have been converging on performance of models that require large amounts of labeled data.

Alexandr Wang is a billionaire who made his wealth through a data labeling company and basically kicked LeCunn out.

Overall this will be good for AI and good for open source.

Re: Yann LeCun raises $1B to build AI that understands the physical world

#198

Post by vidarh »

mfru wrote: post #180
andrepd wrote: post #126

Earlier quoted context omitted.

It's been 6 months away for 5 years now. In that time we've seen relatively mild incremental changes, not any qualitative ones. It's probably not 6 months away.

Reminds me of how cold fusion reactors are only 5 years away for decades now

Cold fusion reactors haven't produced usable intermediate results. LLMs have.

Re: Yann LeCun raises $1B to build AI that understands the physical world

#199

Post by LarsDu88 »

energy123 wrote: post #34
A_D_E_P_T wrote: post #11

Justifiable. There are a lot more degrees of freedom in world models. LLMs are fundamentally capped because they only learn from static text -- human communications about the world -- rather than from the world itself, which is why they can remix existing ideas but find it all but impossible to produce genuinely novel discoveries or inventions. A well-funded and well-run startup building physical world models (ground…

why LLMs (transformers trained on multimodal token sequences, potentially containing spatiotemporal information) can't be a world model?

I really hate the world model terminology, but the actual low level gripe between LeCunn and autoregressive LLMs as they stand now is the fact that the loss function needs to reconstruct the entirety of the input. Anything less than pixel perfect reconstruction on images is penalized. Token by token reconstruction also is biased towards that same level of granularity.

The density of information in the spatiotemporal world is very very great, and a technique is needed to compress that down effectively. JEPAs are a promising technique towards that direction, but if you're not reconstructing text or images, it's a bit harder for humans to immediately grok whether the model is learning something effectively.

I think that very soon we will see JEPA based language models, but their key domain may very well be in robotics where machines really need to experience and reason about the physical the world differently than a purely text based world.

Re: Yann LeCun raises $1B to build AI that understands the physical world

#200

Post by vidarh »

jsnell wrote: post #117
ZeroCool2u wrote: post #32

Regardless of your opinion of Yann or his views on auto regressive models being "sufficient" for what most would describe as AGI or ASI, this is probably a good thing for Europe. We need more well capitalized labs that aren't US or China centric and while I do like Mistral, they just haven't been keeping up on the frontier of model performance and seem like they've sort of pivoted into being integration specialists a…

I don't think it's "regardless", your opinion on LeCun being right should be highly correlated to your opinion on whether this is good for Europe. If you think that LLMs are sufficient and RSI is imminent (<1 year), this is horrible for Europe. It is a distracting boondoggle exactly at the wrong time.

It's sufficient to think that there is a chance that they will not be, however, for there to be a non-zero value to fund other approaches.

And even if you think the chance is zero, unless you also think there is a zero chance they will be capable of pivoting quickly, it might still be beneficial.

I think his views are largely flawed, but chances are there will still be lots of useful science coming out of it as well. Even if current architectures can achieve AGI, it does not mean there can't also be better, cheaper, more effective ways of doing the same things, and so exploring the space more broadly can still be of significant value.

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