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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

#431

Post by carra »

voxleone wrote: post #422

I rank with those who think human-like intelligence will require embeddings grounded in multiple physical sensory domains (vision, touch, audio, chemical sensing, etc.) fused into a shared world representation. That seems much closer to how biological intelligence works than text-only models. But if this path succeeds and produces systems with something like genuine understanding or sentience, there’s a deeper questi…

I don't think they will have sentience or agency unless they are designed to:

1) Keep thinking continuously, as opposed to current AIs that stop functioning between prompts. 2) Have permanent memory of their previous experiences. 3) Be able to alter their own weights based on those experiences (a.k.a. learn).

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

#432

Post by confidantlake »

djeastm wrote: post #425
voxleone wrote: post #422

I rank with those who think human-like intelligence will require embeddings grounded in multiple physical sensory domains (vision, touch, audio, chemical sensing, etc.) fused into a shared world representation. That seems much closer to how biological intelligence works than text-only models. But if this path succeeds and produces systems with something like genuine understanding or sentience, there’s a deeper questi…

It's an interesting question. On one hand we don't worry about this much with animals, the most advanced of which we know have personalities, moods, etc (Pigs, for instance). They really only seem to lack the language and higher-order reasoning skills. But where's the line?

And while they don't have language like we do, dogs can understand basic commands and they aren't even the smartest animals.

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

#433

Post by re5i5tor »

voxleone wrote: post #422

I rank with those who think human-like intelligence will require embeddings grounded in multiple physical sensory domains (vision, touch, audio, chemical sensing, etc.) fused into a shared world representation. That seems much closer to how biological intelligence works than text-only models. But if this path succeeds and produces systems with something like genuine understanding or sentience, there’s a deeper questi…

Does anyone else see an echo of Severance (Apple TV series) here?

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

#434

Post by eloisant »

jacquesm wrote: post #311
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…

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 a…

They can write to files then refer to them in a next session.

A bit like the main character played by Guy Pierce in the movie Memento (which doesn't work great for him to be honest).

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

#435

Post by boringg »

voxleone wrote: post #422

I rank with those who think human-like intelligence will require embeddings grounded in multiple physical sensory domains (vision, touch, audio, chemical sensing, etc.) fused into a shared world representation. That seems much closer to how biological intelligence works than text-only models. But if this path succeeds and produces systems with something like genuine understanding or sentience, there’s a deeper questi…

Its interesting that you seem to be more concerned that we would potentially enslave human like robots (while arguing sentience) while the likelihood of events is that we are far more likely to be enslaved to/by our own creations.

Id say probability wise we don’t create sentient like behavior for a long time (low probability) much higher is the second circumstance.

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

#436

Post by snek_case »

_giorgio_ wrote: post #408

LeCun has had every advantage imaginable — and the scoreboard remains empty. He joined Facebook (now Meta) in December 2013. That's over 12 years of access to one of the largest AI labs in the world, near-unlimited compute, and some of the best researchers money can buy. He introduced I-JEPA in 2023, nearly 3 years ago . It was supposed to represent a fundamental shift in how machines learn — moving beyond generative…

First, believe it or not, 3 years is not that long. It's also not a given that LeCun was given the resources he needed to work on this tech at Meta. Zuck wanted another llama.

Second, AMI Labs just secured a billion in funding, and while that's a lot of money, it's literally just a fraction of the yearly salary they are paying to Wang. Big tech companies are literally throwing tens of billions to keep doing the same thing, just on a bigger scale. Why not try something else once in a while?

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

#437

Post by Nevermark »

jonahx wrote: post #337
perfmode wrote: post #232

Earlier quoted context omitted.

Humans are notoriously bad at formal logic. 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. That looks a lot more like pattern matching than rule application. Kahneman’s whole framework points the same direction. Most of what people call “reasoning” is fast, associative, pattern-based. T…

> The story that humans have access to some pure deductive engine and LLMs are just faking it with statistics might be flattering to humans more than it’s accurate. Your point rings true with most human reasoning most of the time. Still, at least some humans do have the capability to run that deductive engine, and it seems to be a key part (though not the only part) of scientific and mathematical reasoning. Even info…

The fact that humans can learn to do X, sometimes well, often badly, and while many don’t, strongly supports the conjecture that X is not how they naturally do things.

I can perform symbolic calculations too. But most people have limited versions of this skill, and many people who don’t learn to think symbolically have full lives.

I think it is fair to say humans don’t naturally think in formal or symbolic reasoning terms.

People pattern match,

Another clue is humans have to practice things, become familiar with them to reason even somewhat reliable about them. Even if they already learned some formal reasoning.

—-

Higher level reasoning is always implemented as specific forms of lower order reasoning.

There is confusion about substrate processing vs. what higher order processes can be created with that substrate.

We can “just” be doing pattern matching from an implementation view, and yet go far “beyond” pattern matching with specific compositions of pattern matching, from a capability view.

How else could neurons think? We are “only” neurons. Yet we far surpass the kinds of capabilities neurons have.

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

#438

Post by khafra »

echelon wrote: post #355
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…

You have to understand the strategy of all the other players: Build attention-grabbing, monetizable models that subsidize (at least in part) the run up to AGI. Nobody is trying to one-shot AGI. They're grinding and leveling up while (1) developing core competencies around every aspect of the problem domain and (2) winning users. I don't know if Meta is doing a good job of this, but Google, Anthropic, and OpenAI are.…

I mean, Sutskevar and Carmack are trying to one-shot AGI. We just don't talk about them as much as we do the labs with products because their labs aren't selling products.

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

#439

Post by snek_case »

carra wrote: post #431
voxleone wrote: post #422

I rank with those who think human-like intelligence will require embeddings grounded in multiple physical sensory domains (vision, touch, audio, chemical sensing, etc.) fused into a shared world representation. That seems much closer to how biological intelligence works than text-only models. But if this path succeeds and produces systems with something like genuine understanding or sentience, there’s a deeper questi…

I don't think they will have sentience or agency unless they are designed to: 1) Keep thinking continuously, as opposed to current AIs that stop functioning between prompts. 2) Have permanent memory of their previous experiences. 3) Be able to alter their own weights based on those experiences (a.k.a. learn).

That's the direction the field is already going with "agents". People want autonomous AI agents that are capable of acting independently and that have more and more capabilities. For example, something like Claude code, but that acts as a sidekick that is constantly running, and able to act without being prompted. That's what people are imagining when they talk about teams of agents. You act as a manager, but your coding agents are off working on various features and only check in periodically.
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