It includes a grasp of simple physics: for example, knowing that the world is three-dimensional and that objects don’t actually disappear when they go out of view. “Common sense” is the catch-all term for this kind of intuitive reasoning. Seeing a dropped ball fall a handful of times is enough to give a child a sense of how gravity works. Infants pick up the basics in the first few months of life by observing the world, says LeCun. Learned in infancy, it’s the way animals (including humans) make good guesses about what’s going on around them. LeCun thinks that animal brains run a kind of simulation of the world, which he calls a world model. “Getting machines to behave like humans and animals has been the quest of my life,” he says. In 2018 he was joint winner of computing’s top prize, the Turing Award, with Bengio and Geoffrey Hinton, for his pioneering work on deep learning. LeCun has been thinking about AI for nearly 40 years. “People talk about these things in private, but they’re not usually shared publicly,” says Bengio. It’s a research proposal rather than a set of clean results, he says. He also thinks it’s great that LeCun is willing to put out a document that has so few answers. “But it is good to see it all together, in one big picture.” Bengio thinks that LeCun asks the right questions. “Yann has been talking about many of these ideas for some time,” says Yoshua Bengio, an AI researcher at the University of Montreal and scientific director at the Mila-Quebec Institute. ![]() “For those to be most useful to us, they basically have to have more or less human-level intelligence,” he says. ![]() He says that in 10 or 15 years people won’t be carrying smartphones in their pockets, but augmented-reality glasses fitted with virtual assistants that will guide humans through their day. His vision is colored by that of his employer, Meta, which is pushing a virtual-reality metaverse. For LeCun, AGI is going to be a part of how we interact with future tech.
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