Meta’s AI chief says world models are key to ‘human-level AI’ — but it might be 10 years out


Are today’s AI models truly remembering, thinking, planning, and reasoning, just like a human brain would? Some AI labs would have you believe they are, but according to Meta’s chief AI scientist Yann LeCun, the answer is no. He thinks we could get there in a decade or so, however, by pursuing a new method called a “world model.”

Earlier this year, OpenAI released a new feature it calls “memory” that allows ChatGPT to “remember” your conversations. The startup’s latest generation of models, o1, displays the word “thinking” while generating an output, and OpenAI says the same models are capable of “complex reasoning.”

That all sounds like we’re pretty close to AGI. However, during a recent talk at the Hudson Forum, LeCun undercut AI optimists, such as xAI founder Elon Musk and Google DeepMind co-founder Shane Legg, who suggest human-level AI is just around the corner.

“We need machines that understand the world; [machines] that can remember things, that have intuition, have common sense, things that can reason and plan to the same level as humans,” said LeCun during the talk. “Despite what you might have heard from some of the most enthusiastic people, current AI systems are not capable of any of this.”

LeCun says today’s large language models, like those which power ChatGPT and Meta AI, are far from “human-level AI.” Humanity could be “years to decades” away from achieving such a thing, he later said. (That doesn’t stop his boss, Mark Zuckerberg, from asking him when AGI will happen, though.)

The reason why is straightforward: those LLMs work by predicting the next token (usually a few letters or a short word), and today’s image/video models are predicting the next pixel. In other words, language models are one-dimensional predictors, and AI image/video models are two-dimensional predictors. These models have become quite good at predicting in their respective dimensions, but they don’t really understand the three-dimensional world.

Because of this, modern AI systems cannot do simple tasks that most humans can. LeCun notes how humans learn to clear a dinner table by the age of 10, and drive a car by 17 – and learn both in a matter of hours. But even the world’s most advanced AI systems today, built on thousands or millions of hours of data, can’t reliably operate in the physical world.

https://techcrunch.com/2024/10/16/metas-ai-chief-says-world-models-are-key-to-human-level-ai-but-it-might-be-10-years-out/