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by Schlagbohrer
54 days ago
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Geoffrey Hinton said that the breakthrough the AlphaGo team had was getting it to play against itself and improve in that means, since it could then go beyond the human training data it had learned on. He said that an equivalent form of self-training for generalized information would let a superintelligence take off (this is from my memory, not an exact quote). The TechCrunch article doesn't specify how/what kind of data a recursive general AI could use to achieve such a thing. If it is possible that's exciting. Seems like a real philosophical question to answer- How could a general AI self-train? |
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>...Here we show that it is possible for machines to discover a state-of-the-art RL rule that outperforms manually designed rules. This was achieved by meta-learning from the cumulative experiences of a population of agents across a large number of complex environments... https://www.nature.com/articles/s41586-025-09761-x
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>A new generation of agents will acquire superhuman capabilities by learning predominantly from experience. This note explores the key characteristics that will define this upcoming era. https://storage.googleapis.com/deepmind-media/Era-of-Experie...