Geoffrey Hinton’s point is that AI progress is no longer bottlenecked by compute alone it’s bottlenecked by data. The open internet that fueled early breakthroughs has been largely consumed, while the most valuable data now sits behind corporate walls. Simply scaling on scraped text won’t deliver the next leap. His proposed path forward is models learning by thinking, not just reading. By generating new training data through reasoning, experimentation, and self-play, AI can move beyond imitation
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Geoffrey Hinton’s point goes beyond robotics he’s challenging how we define real understanding. Humans learn by interacting with the physical world, not by reading about it. Intelligence emerges from experiments, mistakes, and feedback, not from static information. What surprises researchers is that large language models, trained only on text, have begun to display an unexpected grasp of spatial and physical concepts. That raises a deeper question: how much of “understanding” comes from experien
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