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The man who taught AI to learn believes human-level intelligence is closer than you think | IBM

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Richard Sutton, one of the pioneers behind modern artificial intelligence, is not convinced that simply throwing more computing power at AI will lead to machines that think like humans. In fact, he argues today’s obsession with scaling up deep learning might be holding AI back from its full potential. Sutton, alongside his longtime collaborator Andrew Barto, won this year’s Turing Award—often called the "Nobel Prize of Computing"—for his work in reinforcement learning. He believes the real breakthrough will come when AI stops relying on curated datasets and starts learning from experience, much like a child does. “If we want real intelligence, AI needs to learn by doing, by trial and error,” Sutton said in an interview. “Computation is not a panacea. More compute helps, but it's not the core ingredient of intelligence.” It’s a bold claim at a time when AI giants like OpenAI, Google DeepMind and Anthropic are racing to scale their models, feeding them ever-increasing amounts of data and

The man who taught AI to learn believes human-level intelligence is closer than you think | IBM Tags Artificial intelligence The man who taught AI to learn believes human-level intelligence is closer than you think Author Sascha Brodsky Staff Writer IBM Richard Sutton, one of the pioneers behind modern artificial intelligence, is not convinced that simply throwing more computing power at AI will lead to machines that think like humans. In fact, he argues today’s obsession with scaling up deep learning might be holding AI back from its full potential. Sutton, alongside his longtime collaborator

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