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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

#341

Post by mxkopy »

andy12_ wrote: post #30
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…

I don't understand this view. How I see it the fundamental bottleneck to AGI is continual learning and backpropagation. Models today are static, and human brains don't learn or adapt themselves with anything close to backpropagation. World models don't solve any of these problems; they are fundamentally the same kind of deep learning architectures we are used to work with. Heck, if you think learning from the world i…

The reason LLMs fail today is because there’s no meaning inherent to the tokens they produce other than the one captured by cooccurrence within text. Efforts like these are necessary because so much of “general intelligence” is convention defined by embodied human experience, for example arrows implying directionality and even directionality itself.

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

#342

Post by halayli »

I feel HN comments have been getting hijacked for a long time now by LLM agents. Always so early, very positive, and hard to spot. Some replaced em-dash with --, some replace them with a single dash, some remove them all together. I wonder how much time it is taking from @dang and other moderators helping to maintain this community.

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

#343

Post by uoaei »

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…

> There are a lot more degrees of freedom in world models.

Perhaps for the current implementations this is true. But the reason the current versions keep failing is that world dynamics has multiple orders of magnitude fewer degrees of freedom than the models that are tasked to learn them. We waste so much compute learning to approximate the constraints that are inherent in the world, and LeCun has been pressing the point the past few years that the models he intends to design will obviate the excess degrees of freedom to stabilize training (and constrain inference to physically plausible states).

If my assumption is true then expect Max Tegmark to be intimately involved in this new direction.

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

#344

Post by sothatsit »

HarHarVeryFunny wrote: post #288
sothatsit wrote: post #241

Earlier quoted context omitted.

RL on LLMs has changed things. LLMs are not stuck in continuation predicting territory any more. Models build up this big knowledge base by predicting continuations. But then their RL stage gives rewards for completing problems successfully. This requires learning and generalisation to do well, and indeed RL marked a turning point in LLM performance. A year after RL was made to work, LLMs can now operate in agent har…

RL adds a lot of capability in the areas where it can be applied, but I don't think it really changes the fundamental nature of LLMs - they are still predicting training set continuations, but now trying to predict/select continuations that amount to reasoning steps steering the output in a direction that had been rewarded during training. At the end of the day it's still copying, not learning. RL seems to mostly onl…

You can’t really say it is just predicting continuations when it is learning to write proofs for Erdos problems, formalise significant math results, or perform automated AI research. Those are far beyond what you get by just being a copying and re-forming machine, a lot of these problems require sophisticated application of logic.

I don’t know if this can reach AGI, or if that term makes any sense to begin with. But to say these models have not learnt from their RL seems a bit ludicrous. What do you think training to predict when to use different continuations is other than learning?

I would say LLM’s failure cases like failing at riddles are more akin to our own optical illusions and blind spots rather than indicative of the nature of LLMs as a whole.

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

#345

Post by oefrha »

rockinghigh wrote: post #325
oefrha wrote: post #88

Earlier quoted context omitted.

Llama wasn’t Yann LeCun’s work and he was openly critical of LLMs, so it’s not very relevant in this context. Source: himself https://x.com/ylecun/status/1993840625142436160 (“I never worked on any Llama.”) and a million previous reports and tweets from him.

He founded FAIR and the team in Paris that ultimately worked on the early Llama versions.

FAIR was founded in 2015 and Llama's first release was in 2023. Musk co-founded OpenAI in 2015 but no reasonable person credits ChatGPT in 2022 to him.

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

#346

Post by cindyllm »

sothatsit wrote: post #344
HarHarVeryFunny wrote: post #288

Earlier quoted context omitted.

RL adds a lot of capability in the areas where it can be applied, but I don't think it really changes the fundamental nature of LLMs - they are still predicting training set continuations, but now trying to predict/select continuations that amount to reasoning steps steering the output in a direction that had been rewarded during training. At the end of the day it's still copying, not learning. RL seems to mostly onl…

You can’t really say it is just predicting continuations when it is learning to write proofs for Erdos problems, formalise significant math results, or perform automated AI research. Those are far beyond what you get by just being a copying and re-forming machine, a lot of these problems require sophisticated application of logic. I don’t know if this can reach AGI, or if that term makes any sense to begin with. But…

[dead]

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

#347

Post by hdivider »

It's curious to me why we have no theory of intelligence. By which I mean an actual hard and verified theory, as in physics for gravity, electromagnetism, quantum mechanics.

Intelligence is simply not well-understood at a mathematical level. Like medieval engineers, we rely so heavily on experimentation in AI. We have no idea how far away from the human level we actually are. Or how far above the human level we can get. Or what, if anything, the limits of intelligence are.

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

#348

Post by sinuhe69 »

vrganj wrote: post #301
az226 wrote: post #104

Yann LeCun seeks $5B+ valuation for world model startup AMI (Amilabs). He has hired LeBrun to the helm as CEO. AMI has also hired LeFunde as CFO and LeTune as head of post-training. They’re also considering hiring LeMune as Head of Growth and LePrune to lead inference efficiency. https://techcrunch.com/2025/12/19/yann-lecun-confirms-his-ne...

The guy overseeing the funds is called Le Fund e and the guy doing the fine-tuning Le Tune ??

He just made a joke

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

#349

Post by jimbokun »

hdivider wrote: post #347

It's curious to me why we have no theory of intelligence. By which I mean an actual hard and verified theory, as in physics for gravity, electromagnetism, quantum mechanics. Intelligence is simply not well-understood at a mathematical level. Like medieval engineers, we rely so heavily on experimentation in AI. We have no idea how far away from the human level we actually are. Or how far above the human level we can g…

By now you would have to say it’s because “intelligence” is no more well defined than “consciousness” or “the soul”.

A more concrete idea like “learning” has been very strongly defined and quantifiable, which is maybe why progress in a theory of learning is so much more advanced than a theory of “intelligence“.

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

#350

Post by dang »

halayli wrote: post #342

I feel HN comments have been getting hijacked for a long time now by LLM agents. Always so early, very positive, and hard to spot. Some replaced em-dash with --, some replace them with a single dash, some remove them all together. I wonder how much time it is taking from @dang and other moderators helping to maintain this community.

Can you mention some specific examples? If you don't want to post them here, emailing hn@ycombinator.com would be good.

We recently promoted the no-generated-comments rule from case law [1] to the site guidelines [2], and we're banning accounts that break it.

[1] https://hn.algolia.com/?dateRange=all&page=0&prefix=true&que...

[2] https://news.ycombinator.com/newsguidelines.html#generated

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