Yann LeCun Rejects AGI as Demis Hassabis Calls Him “Plain Incorrect”

A heated public debate erupted on X (formerly Twitter) on December 23, 2025, between two of the most influential figures in artificial intelligence: Demis Hassabis, CEO of Google DeepMind and co-recipient of the 2024 Nobel Prize in Chemistry for his work on protein folding, and Yann LeCun, often called the "Godfather of AI" and former Chief AI Scientist at Meta. The exchange centered on the very concept of general intelligence and whether artificial general intelligence (AGI) is even possible, quickly escalating into a sharp war of words between the two pioneers.

The debate was sparked when Demis Hassabis asserted that general intelligence exists as a real phenomenon, pointing to human intelligence as proof. He argued that the human brain operates like a Turing machine—a universal computational system capable of performing any conceivable calculation—and that this provides a clear pathway toward building AGI. Hassabis directly countered LeCun's long-standing skepticism, stating that his counterpart was "plain incorrect" in denying the existence of general intelligence as a coherent concept.

Yann LeCun responded forcefully, maintaining that general intelligence as commonly understood is not achievable. His core argument is that true general intelligence cannot be built because humans themselves cannot even clearly define or imagine what it fully entails beyond narrow, task-specific capabilities. LeCun has long argued that the human brain, while remarkable, is highly inefficient compared to engineered systems, relying on massive energy consumption and slow processing relative to its output. He has repeatedly expressed doubts about the feasibility of AGI in the near or even medium term, viewing many current claims as overhyped.

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The exchange quickly drew widespread attention across the AI community and social media, with observers noting the irony of two leading minds—one heading Google DeepMind's aggressive push toward advanced AI systems and the other now running his own startup, Advanced Machine Intelligence (AMI) Labs—clashing over the foundational premise of their life's work. The public spat has reignited broader discussions about the timelines, definitions, and even the desirability of achieving AGI, especially as major players race to develop increasingly powerful models.

While the argument remained civil in tone, it highlighted deep philosophical and technical divides within the field. Hassabis represents the more optimistic camp that believes scaling current architectures, combined with breakthroughs in reasoning and world-modeling, can lead to human-level intelligence. LeCun, conversely, advocates for a more grounded approach, criticizing what he sees as overreliance on large language models and calling for fundamentally new paradigms to move beyond narrow AI.

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