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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

#311

Post by jacquesm »

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 main difference is humans are learning all the time and models learn batch wise and forget whatever happened in a previous session unless someone makes it part of the training data so there is a massive lag.

Whoever cracks the continuous customized (per user, for instance) learning problem without just extending the context window is going to be making a big splash. And I don't mean cheats and shortcuts, I mean actually tuning the model based on received feedback.

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

#312

Post by jacquesm »

lugu wrote: post #296
lich_king wrote: post #243

Earlier quoted context omitted.

> The Wason selection task is the classic example: most people fail a simple conditional reasoning problem unless it’s dressed up in familiar social context, like catching cheaters. I've never heard about the Wason selection task, looked it up, and could tell the right answer right away. But I can also tell you why: because I have some familiarity with formal logic and can, in your words, pattern-match the gotcha tha…

Your response contains a performative contradiction: you are asserting that humans are naturally logical while simultaneously committing several logical errors to defend that claim.

This comment would be a lot more useful with an enumeration of those logical errors.

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

#313

Post by Bombthecat »

10xDev wrote: post #12
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…

Whether it is text or an image, it is just bits for a computer. A token can represent anything.

Can a token represent concentration, will?

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

#314

Post by yalok »

chriskanan wrote: post #284

I had lunch with Yann last August, about a week after Alex Wang became his "boss." I asked him how he felt about that, and at the time he told me he would give it a month or two and see how it goes, and then figure out if he should stay or find employment elsewhere. I told him he ought to just create his own company if he decides to leave Meta to chase his own dream, rather than work on the dream's of others. That sa…

> I'm not fully on board with his world model strategy as the path forward

can you please elaborate on your strategy as the path forward?

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

#315

Post by infinite8s »

jandrewrogers wrote: post #303
MITSardine wrote: post #280

Earlier quoted context omitted.

> 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. What do you mean by that? Simulating physics is a rich field, which incidentally was one of the main drivers of parallel/super computing before AI came along.

The mapping of the physical world onto a computer representation introduces idiosyncratic measurement issues for every data point. The idiosyncratic bias, errors, and non-repeatability changes dynamically at every point in space and time, so it can be modeled neither globally nor statically. Some idiosyncratic bias exhibits coupling across space and time. Reconstructing ground truth from these measurements, which is…

Is this like some scale-independent version of Heisenberg's Uncertainty Principle?

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

#317

Post by lich_king »

lugu wrote: post #296
lich_king wrote: post #243

Earlier quoted context omitted.

> The Wason selection task is the classic example: most people fail a simple conditional reasoning problem unless it’s dressed up in familiar social context, like catching cheaters. I've never heard about the Wason selection task, looked it up, and could tell the right answer right away. But I can also tell you why: because I have some familiarity with formal logic and can, in your words, pattern-match the gotcha tha…

Your response contains a performative contradiction: you are asserting that humans are naturally logical while simultaneously committing several logical errors to defend that claim.

When someone tells you "you can have this if you pay me", they don't mean "you can also have it if you don't pay". They are implicitly but clearly indicating you gotta pay.

It's as simple as that. In common use, "if x then y" frequently implies "if not x then not y". Pretending that it's some sort of a cognitive defect to interpret it this way is silly.

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