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

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201–210 of 529 posts

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

#201
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…

That's such a terrible take.

For a hot minute Meta had a top 3 LLM and open sourced the whole thing, even with LeCunn's reservations around the technology.

At the same time Meta spat out huge breakthroughs in:

- 3d model generation

- Self-supervised label-free training (DINO). Remember Alexandr Wang built a multibillion dollar company just around having people in third world countries label data, so this is a huge breakthrough.

- A whole new class of world modeling techniques (JEPAs)

- SAM (Segment anything)

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

#202
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.

Whenever I see claims about AGI being reachable through large language models, it reminds me of the miasma theory of disease. Many respectable medical professionals were convinced this was true, and they viewed the entire world through this lens. They interpreted data in ways that aligned with a miasmatic view. Of course now we know this was delusional and it seems almost funny in retrospect. I feel the same way when…

> Whenever I see claims about AGI being reachable through large language models, it reminds me of the miasma theory of disease.

Whenever I see people think the model architecture matters much, I think they have a magical view of AI. Progress comes from high quality data, the models are good as they are now. Of course you can still improve the models, but you get much more upside from data, or even better - from interactive environments. The path to AGI is not based on pure thinking, it's based on scaling interaction.

To remain in the same miasma theory of disease analogy, if you think architecture is the key, then look at how humans dealt with pandemics... Black Death in the 14th century killed half of Europe, and none could think of the germ theory of disease. Think about it - it was as desperate a situation as it gets, and none had the simple spark to keep hygiene.

The fact is we are also not smart from the brain alone, we are smart from our experience. Interaction and environment are the scaffolds of intelligence, not the model. For example 1B users do more for an AI company than a better model, they act like human in the loop curators of LLM work.

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

#203

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…

> fully ceding the research front is not a good way to keep the EU competitive

Tech is ultimately a red herring as far as what's needed to keep the EU competitive. The EU has a trillion dollar hole[0] to fill if they want to replace US military presence, and current net import over 50% of their energy. Unfortunately the current situation in Iran is not helping either of these as they constrains energy further and risks requiring military intervention.

0. https://www.wsj.com/world/europe/europes-1-trillion-race-to-...

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

#204

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…

> 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.

No hate, but this is just your opinion.

The definition of "text" here is extremely broad – an SVG is text, but it's also an image format. It's not incomprehensible to imagine how an AI model trained on lots of SVG "text" might build internal models to help it "visualise" SVGs in the same way you might visualise objects in your mind when you read a description of them.

The human brain only has electrical signals for IO, yet we can learn and reason about the world just fine. I don't see why the same wouldn't be possible with textual IO.

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

#205

Earlier quoted context omitted.

Sure! Here’s a description: https://www.empirical.health/blog/wearable-foundation-model-...

Thanks! This is very neat. BTW, I went to your website looking for this, but didn't find your blog. I do now see that it's linked in the footer, but I was looking for it in the hamburger menu.

Thanks! We need to re-do the top navigation / hamburger menu -- we've added a bunch of new things in the past few months, and it badly needs to be re-organized.

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

#206

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…

> fully ceding the research front is not a good way to keep the EU competitive Tech is ultimately a red herring as far as what's needed to keep the EU competitive. The EU has a trillion dollar hole[0] to fill if they want to replace US military presence, and current net import over 50% of their energy. Unfortunately the current situation in Iran is not helping either of these as they constrains energy further and ris…

Right, they really need a military industrial complex to be "competitive" :eyeroll. Are you suggesting regressing to the stone age?

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

#207

Earlier quoted context omitted.

I have a pet peeve with the concept of "a genuinely novel discovery or invention", what do you imagine this to be? Can you point me towards a discovery or invention that was "genuinely novel", ever? I don't think it makes sense conceptually unless you're literally referring to discovering new physical things like elements or something. Humans are remixers of ideas. That's all we do all the time. Our thoughts and acti…

Genuinely novel discovery or invention? Einstein’s theory of relativity springs to mind, which is deeply counter-intuitive and relies on the interaction of forces unknowable to our basic Newtonian senses. There’s an argument that it’s all turtles (someone told him about universes, he read about gravity, etc), but there are novel maths and novel types of math that arise around and for such theories which would indicat…

Nah - Poincare & Lorentz did quite a bit of groundwork on relativity and its implications before Einstein put it all together.

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

#208
post #139

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…

The sum of human knowledge is more than enough to come up with innovative ideas and not every field is working directly with the physical world. Still I would say there's enough information in the written history to create virtual simulation of 3d world with all ohysical laws applying (to a certain degree because computation is limited). What current LLMs lack is inner motivation to create something on their own with…

> virtual simulation of 3d world

Virtual simulations are not substitutable for the physical world. They are fundamentally different theory problems that have almost no overlap in applicability. You could in principle create a simulation with the same mathematical properties as the physical world but no one has ever done that. I'm not sure if we even know how.

Physical world dynamics are metastable and non-linear at every resolution. The models we do build are created from sparse irregular samples with large error rates; you often have to do complex inference to know if a piece of data even represents something real. All of this largely breaks the assumptions of our tidy sampling theorems in mathematics. The problem of physical world inference has been studied for a couple decades in the defense and mapping industries; we already have a pretty good understanding of why LLM-style AI is uniquely bad at inference in this domain, and it mostly comes down to the architectural inability to represent it.

Grounded estimates of the minimum quantity of training data required to build a reliable model of physical world dynamics, given the above properties, is many exabytes. This data exists, so that is not a problem. The models will be orders of magnitude larger than current LLMs. Even if you solve the computer science and theory problems around representation so that learning and inference is efficient, few people are prepared for the scale of it.

(source: many years doing frontier R&D on these problems)

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

#209

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…

33% of the business in a seed round is nuts

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

#210

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…

33% of the business in a seed round is nuts

can you elaborate more, also isn't this necessary for a Lab that wants to compete with highly funded entities (like OpenAI, Anthropic)?
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