Yann LeCun

Language is a very approximate representation of our percepts and our mental models. There's a lot of tasks that we accomplish where we manipulate a mental model of the situation at hand, and that has nothing to do with language. Everything that's physical, mechanical, whatever, when we build something, when we accomplish a task, a model task of grabbing something, etc.,

Language is a very approximate representation of our percepts and our mental models. There's a lot of tasks that we accomplish where we manipulate a mental model of the situation at hand, and that has nothing to do with language. Everything that's physical, mechanical, whatever, when we build something, when we accomplish a task, a model task of grabbing something, etc.,

Language is a very approximate representation of our percepts and our mental models. There's a lot of tasks that we accomplish where we manipulate a mental model of the situation at hand, and that has nothing to do with language. Everything that's physical, mechanical, whatever, when we build something, when we accomplish a task, a model task of grabbing something, etc.,

We plan our action sequences, and we do this by essentially imagining the result of the outcome of a sequence of actions that we might imagine. And that requires mental models that don't have much to do with language. And that's, I would argue, most of our knowledge is derived from that interaction with the physical world.

We plan our action sequences, and we do this by essentially imagining the result of the outcome of a sequence of actions that we might imagine. And that requires mental models that don't have much to do with language. And that's, I would argue, most of our knowledge is derived from that interaction with the physical world.

We plan our action sequences, and we do this by essentially imagining the result of the outcome of a sequence of actions that we might imagine. And that requires mental models that don't have much to do with language. And that's, I would argue, most of our knowledge is derived from that interaction with the physical world.

So a lot of my colleagues who are more interested in things like computer vision are really on that camp that AI needs to be embodied, essentially. And then other people coming from the NLP side or maybe some other motivation don't necessarily agree with that. And philosophers are split as well. And the complexity of the world is hard to imagine. It's hard to

So a lot of my colleagues who are more interested in things like computer vision are really on that camp that AI needs to be embodied, essentially. And then other people coming from the NLP side or maybe some other motivation don't necessarily agree with that. And philosophers are split as well. And the complexity of the world is hard to imagine. It's hard to

So a lot of my colleagues who are more interested in things like computer vision are really on that camp that AI needs to be embodied, essentially. And then other people coming from the NLP side or maybe some other motivation don't necessarily agree with that. And philosophers are split as well. And the complexity of the world is hard to imagine. It's hard to

represent all the complexities that we take completely for granted in the real world that we don't even imagine require intelligence, right? This is the old Moravec paradox from the pioneer of robotics, Hans Moravec, who said, you know, how is it that with computers it seems to be easy to do high-level complex tasks like playing chess and solving integrals and doing things like that, whereas

represent all the complexities that we take completely for granted in the real world that we don't even imagine require intelligence, right? This is the old Moravec paradox from the pioneer of robotics, Hans Moravec, who said, you know, how is it that with computers it seems to be easy to do high-level complex tasks like playing chess and solving integrals and doing things like that, whereas

represent all the complexities that we take completely for granted in the real world that we don't even imagine require intelligence, right? This is the old Moravec paradox from the pioneer of robotics, Hans Moravec, who said, you know, how is it that with computers it seems to be easy to do high-level complex tasks like playing chess and solving integrals and doing things like that, whereas

The thing we take for granted that we do every day, like, I don't know, learning to drive a car or, you know, grabbing an object. We can't do it with computers. And, you know, we have LLMs that can pass the bar exam. So they must be smart. But then they can't learn to drive in 20 hours like any 17-year-old.

The thing we take for granted that we do every day, like, I don't know, learning to drive a car or, you know, grabbing an object. We can't do it with computers. And, you know, we have LLMs that can pass the bar exam. So they must be smart. But then they can't learn to drive in 20 hours like any 17-year-old.

The thing we take for granted that we do every day, like, I don't know, learning to drive a car or, you know, grabbing an object. We can't do it with computers. And, you know, we have LLMs that can pass the bar exam. So they must be smart. But then they can't learn to drive in 20 hours like any 17-year-old.

They can't learn to clear out the dinner table and fill up the dishwasher like any 10-year-old can learn in one shot. Why is that? Like, you know, what are we missing? What type of learning or reasoning architecture or whatever are we missing that basically prevent us from, you know, having level five self-driving cars and domestic robots?

They can't learn to clear out the dinner table and fill up the dishwasher like any 10-year-old can learn in one shot. Why is that? Like, you know, what are we missing? What type of learning or reasoning architecture or whatever are we missing that basically prevent us from, you know, having level five self-driving cars and domestic robots?

They can't learn to clear out the dinner table and fill up the dishwasher like any 10-year-old can learn in one shot. Why is that? Like, you know, what are we missing? What type of learning or reasoning architecture or whatever are we missing that basically prevent us from, you know, having level five self-driving cars and domestic robots?

So yeah, that's what a lot of people are working on. So the short answer is no. And the more complex answer is you can use all kinds of tricks to get an LLM to basically digest visual representations of images Or video, or audio for that matter. And a classical way of doing this is you train a vision system in some way.

So yeah, that's what a lot of people are working on. So the short answer is no. And the more complex answer is you can use all kinds of tricks to get an LLM to basically digest visual representations of images Or video, or audio for that matter. And a classical way of doing this is you train a vision system in some way.