June 2022 Around a year and a half ago, Yann LeCun realized he had it wrong. LeCun, who is chief scientist at Meta's AI lab and a professor at New York University, is one of the most influential AI researchers in the world. He had been trying to give machines a basic grasp of how the world works--a kind of common sense--by training neural networks to predict what was going to happen next in video clips of everyday events. But guessing future frames of a video pixel by pixel was just too complex. Now, after months figuring out what was missing, he has a bold new vision for the next generation of AI, which he thinks will one day give machines the common sense they need to navigate the world.

Around a year and a half ago, Yann LeCun realized he had it wrong. LeCun, who is chief scientist at Meta's AI lab and one of the most influential AI researchers in the world, had been trying to give machines a basic grasp of how the world works--a kind of common sense--by training neural networks to predict what was going to happen next in video clips of everyday events. But guessing future frames of a video pixel by pixel was just too complex. Now, after months figuring out what was missing, he has a bold new vision for the next generation of AI. In a draft document shared with MIT Technology Review, LeCun sketches out an approach that he thinks will one day give machines the common sense they need to navigate the world.

"This idea that we're going to just scale up the current large language models and eventually human-level AI will emerge--I don't believe this at all, not for one second." Yann LeCun, chief scientist at Meta's artificial intelligence (AI) lab and one of the world's most influential AI researchers, has a bold new vision for the next generation of AI. In a draft document shared with MIT Technology Review, LeCun sketches out an approach that he thinks will one day give machines the common sense they need to navigate the world. "Getting machines to behave like humans and animals has been the quest of my life," he says. LeCun thinks that animal brains run a kind of simulation of the world, which he calls a world model.

The centerpiece of the new approach is a neural network that can learn to view the world at different levels of detail. Ditching the need for pixel-perfect predictions, this network would focus only on those features in a scene that are relevant for the task at hand. LeCun pairs this core network with another, called the configurator, which determines what level of detail is required and tweaks the overall system accordingly. For LeCun, AGI is going to be a part of how we interact with future tech. His vision is colored by that of his employer, Meta, which is pushing a virtual-reality metaverse.