Meta’s former Chief AI scientist who is also popularly regarded as the Godfather of AI, Yann Lecun, wants AI models to do lots more. In a post on X, formerly Twitter Lecun said that he wants LLMs (Large Language Models) to do a lot more including physical work. He made the comment while replying to Paul Graham. “Someone asked what I’d do if I were 17. I’d learn how to build LLMs from scratch, and then train ones as powerful as I could with whatever hardware I could get access to,” wrote Graham in a post on X.To this Lecun replied, “I would try to figure out why LLMs can write my essays but not clean my bedroom. Then I would study topics in college and grad school that could help solve that problem. I’ll figure out a set of methods and architectures beyond LLMs that can quickly learn to perform physical tasks as efficiently as humans and animals. That last item is also what I would if I were 30, 40, 50, or 66 years old.”
Yann Lecun to Amazon’s Jitendra Malik: I don’t agree with your definition
In a similar context he also replied to his former colleague at Meta Jitendra Malik, who last month left the Facebook-parent to join Amazon’s robotics division. Malik wrote, “Scientific terms should have precision. If we use the terms VLM, VLA, WAM in an indiscriminate fashion, as is becoming common in robotics, we are not helping clarity in communication. Let’s keep the historical origins of these terms in mind. VLMs arose as multimodal extensions of LLMs-the training was for tasks like VQA (VIsual Question Answering). These capture the static semantics of the scene behind an image. No dynamics. World Models (e.g.@ylecun) Ha & Schmidhuber 2018) on the other hand are primarily dynamics models, which go back to control theory -1960 (Bellman, Kalman etc.) This makes them natural for robotics planning / policies- I am in a state s, what action a should I perform to get to state s’. In classical control, these models were written down a priori by modeling the physics of the system; today we think of them as learned neural networks trained from temporal data e.g. video, robot trajectories. But the concept is the same. We shouldn’t mix this concept with VLMs.”Amazon exec tagged Yann Lecun in his post. Lecun disagreed with him on his views on LLMs, VLMs and robotics. He said that he does not agree with Malik’s definition. “Exactly. We also should not confuse world models, as per your definition, with video prediction or video generation models. Understanding the dynamics of a system in order to control it is not the same as producing cute videos,” wrote Lecun.
AI ‘godfather’ leaves Meta after 12 years
For those unaware, Yann LeCun is a French-American computer scientist widely known as one of the Godfathers of AI. He won the 2018 Turing Award for deep learning, created convolutional neural networks (CNNs), served as Meta’s Chief AI Scientist, and is a professor at New York University. In November 2025, Leun announced his planned departure from Meta, the company he has been part of for twelve years. “As many of you have heard through rumours or recent media articles, I am planning to leave Meta after 12 years: 5 years as founding director of FAIR and 7 years as Chief AI Scientist,” he wrote. “The impact of FAIR on the company, on the field of AI, on the tech community, and on the wider world has been spectacular,” he added.