""The reason I tend to steer away from AGI conversations is lots of people have very different definitions of it, and the difficulty of the problem varies by like factors of a trillion," he said. He said AI models today are "probably already" better than the average person at most non-physical tasks. "Most people are not that good at a random task that they've never done before, and some of the models we have today are actually pretty reasonable at most things," he said."
"When asked how far we are from AI being able to make breakthroughs faster than humans, Dean said, "We're actually probably already close to that in some domains." "There will be a lot of domains where automated search and computation actually can accelerate progress - scientific progress, engineering progress," he said. "All these things I think are going to be important for advancing what we as people can do over the next five, 10, 15, 20 years.""
AGI lacks a consistent definition, with difficulty estimates varying by orders of magnitude. Current AI models already exceed average human performance on many non-physical tasks, while still failing at numerous other tasks and lacking world-expert-level capability across all domains. Automated search and computation can accelerate scientific and engineering progress, enabling AI to make breakthroughs faster than humans in some domains. These capabilities are expected to be important for augmenting human productivity and advancing research over the next five to twenty years. Disagreement over AGI definitions persists because some consider it as surpassing the world's experts at every task, while others use looser interpretations.
Read at Business Insider
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