The architect behind much of modern machine learning says the robotics boom rests on shaky ground until a new kind of AI emerges.
Speaking in a dialogue with Mark Gorenberg, chair of the MIT Corporation, Meta Chief AI Scientist Yann LeCun says the entire robotics sector faces a fundamental intelligence gap, one that current models cannot bridge.
LeCun, who pioneered convolutional neural networks and helped shape modern machine learning, says the next generation of systems must move beyond today’s large language models toward what he calls “world models.”
“So this notion of world model… I think [it] is going to be kind of a key component of future AI systems.”
World models are AI systems that can learn to understand and predict the physical world. According to LeCun, the shift from large language models (LLMs) to world models is coming fast, rendering the former obsolete in just a few years.
“And my prediction has been, I’ve been not making friends in various corners of Silicon Valley, including at Meta, saying that within three to five years, this will be the dominant model for AI architectures. And nobody in their right mind would use LLMs of the type that we have today.”
Turning to robotics, the Godfather of deep learning says the industry’s public confidence hides a critical technical failure.
“There is a large number of robotics companies that have been created over the last few years building humanoid robots. The big secret of the industry is that none of those companies has any idea how to make those robots smart enough to be useful, or I should say smart enough to be generally useful.”
He stresses that while task-specific training works in controlled environments, general-purpose capability remains out of reach.
“We can train those robots for particular tasks, maybe in manufacturing and things like this. But your domestic robot, there are a bunch of breakthroughs that need to arrive in AI before that’s possible.”
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