The idea that you're going to extend the capabilities of LLMs [large language models] to the point that they're going to have human-level intelligence is complete nonsense. Most human reasoning is grounded in the physical world, not language, and AI world models are necessary to develop true human-level intelligence.
Big AI companies like OpenAI and Anthropic like to talk about their bold quest for AGI, or artificial general intelligence. The definition of that grail has proved to be somewhat flexible, but in general it refers to AI systems that are as smart as human beings at a wide array of tasks. AI companies have used this "quest" narrative to win investment, fascinate the tech press, and charm policymakers.
LeCun founded Meta's Fundamental AI Research lab, known as FAIR, in 2013 and has served as the company's chief AI scientist ever since. He is one of three researchers who won the 2018 Turing Award for pioneering work on deep learning and convolutional neural networks. After leaving Meta, LeCun will remain a professor at New York University, where he has taught since 2003.
"Geoff is basically proposing a simplified version of what I've been saying for several years: hardwire the architecture of AI systems so that the only actions they can take are towards completing objectives we give them, subject to guardrails."
Countries must ensure they are not impeding open source platforms, as Yann LeCun advocates for collaborative international regulation of open-source AI.
