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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

#171

Post by _giorgio_ »

samrus wrote: post #94
_giorgio_ wrote: post #72

Earlier quoted context omitted.

I can’t reconcile this dichotomy: most of the landmark deep learning papers were developed with what, by today’s standards, were almost ridiculously small training budgets — from Transformers to dropout, and so on. So I keep wondering: if his idea is really that good — and I genuinely hope it is — why hasn’t it led to anything truly groundbreaking yet? It can’t just be a matter of needing more data or more researcher…

Its a matter of needing more time, which is a resource even SV VCs are scared to throw around. Look at the timeline of all these advancements and how long it took Lecun introduced backprop for deep learning back in 1989 Hinton published about contrastive divergance in next token prediction in 2002 Alexnet was 2012 Word2vec was 2013 Seq2seq was 2014 AiAYN was 2017 UnicornAI was 2019 Instructgpt was 2022 This makes alo…

If his ideas had real substance, we would have seen substantial results by now. He introduced I-JEPA in 2023, so almost three years ago at this point.

If he still hasn’t produced anything truly meaningful after all these years at Meta, when is that supposed to happen? Yann LeCun has been at Facebook/Meta since December 2013.

Your chronological sequence is interesting, but it refers to a time when the number of researchers and the amount of compute available were a tiny fraction of what they are today.

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

#172

Post by daxfohl »

energy123 wrote: post #38
andy12_ wrote: post #30

Earlier quoted context omitted.

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…

I don't understand why online learning is that necessary. If you took Einstein at 40 and surgically removed his hippocampus so he can't learn anything he didn't already know (meaning no online learning), that's still a very useful AGI. A hippocampus is a nice upgrade to that, but not super obviously on the critical path.

He basically said that himself:

"Reading, after a certain age, diverts the mind too much from its creative pursuits. Any man who reads too much and uses his own brain too little falls into lazy habits of thinking".

-- Albert Einstein

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

#174

Post by koakuma-chan »

ma2rten wrote: post #159
neversupervised wrote: post #158

Earlier quoted context omitted.

Is it good? This will almost certainly fail. Not because Yann or Europe, but because these sort of hyper-hyped projects fail. SSI and Thinking Machines haven’t lived to the hype.

Erm, ... OpenAI has hyped when it started and it took 6 years to take off. It's way to early to declare the SSI and Thinking Machines have failed.

They took money and haven't released anything. How are they doing?

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

#175

Post by [deleted] »

next_xibalba wrote: post #148
jsnell wrote: post #117

Earlier quoted context omitted.

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.

> RSI Wait, we have another acronym to track. Is this the same/different than AGI and/or ASI?

[deleted]

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

#176

Post by 10xDev »

jnd-cz wrote: post #130
10xDev wrote: post #52

Earlier quoted context omitted.

The fact that models aren't continually updating seems more like a feature. I want to know the model is exactly the same as it was the last time I used it. Any new information it needs can be stored in its context window or stored in a file to read the next it needs to access it.

Unless you use your oen local models then you don't even know when OpenAI or Anthropic tweaked the model less or more. One week it's a version x, next week it's a version y. Just like your operating system is continuously evolving with smaller patches of specific apps to whole new kernel version and new OS release.

There is still a huge gap between a model continuously updating itself and weekly patches by a specialist team. The former would make things unpredictable.

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

#177

Post by andrepd »

basket_horse wrote: post #138
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.

But I swear this time is different! Just give me another 6 months!

And another 6 trillion dollars :^)

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

#178

Post by 10xDev »

kergonath wrote: post #73
10xDev wrote: post #52

Earlier quoted context omitted.

The fact that models aren't continually updating seems more like a feature. I want to know the model is exactly the same as it was the last time I used it. Any new information it needs can be stored in its context window or stored in a file to read the next it needs to access it.

> The fact that models aren't continually updating seems more like a feature. I think this is true to some extent: we like our tools to be predictable. But we’ve already made one jump by going from deterministic programs to stochastic models. I am sure the moment a self-evolutive AI shows up that clears the "useful enough" threshold we’ll make that jump as well.

Stochastic and unpredictability aren't exactly the same. I would claim current LLMs are generally predictable even if it is not as predictable as a deterministic program.

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

#179

Post by HarHarVeryFunny »

lordmathis wrote: post #166
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.

It's 6 months away the same way coding is apparently "solved" now.

I think we - in last few months - are very close to, if not already at, the point where "coding" is solved. That doesn't mean that software design or software engineering is solved, but it does mean that a SOTA model like GPT 5.4 or Opus 4.6 has a good chance of being able to code up a working version of whatever you specify, with reason.

What's still missing is the general reasoning ability to plan what to build or how to attack novel problems - how to assess the consequences of deciding to build something a given way, and I doubt that auto-regressively trained LLMs is the way to get there, but there is a huge swathe of apps that are so boilerplate in nature that this isn't the limitation.

I think that LeCun is on the right track to AGI with JEPA - hardly a unique insight, but significant to now have a well funded lab pursuing this approach. Whether they are successful, or timely, will depend if this startup executes as a blue skies research lab, or in more of an urgent engineering mode. I think at this point most of the things needed for AGI are more engineering challenges rather than what I'd consider as research problems.

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

#180

Post by mfru »

andrepd wrote: post #126
jsnell wrote: post #117

Earlier quoted context omitted.

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 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
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