AI, Machine Learning和Deep Learning的区别
Deep learning的限制
Deep learning usually requires large amounts of training data. Deep learning通常需要更大量的训练数据
Success of deep learning are purely empirical, deep learning algorithms have veen criticized as uninterpretable “black-boxes”. 深度学习的成功纯粹是经验主义的，深度学习算法被批评为无法解释的“黑匣子”。
Deep learning thus far has not been well integrated with prior knowledge. 到目前为止，深度学习还没有很好地与已有知识相结合。
Deep neural networks are easily fooled. 深度神经网络很容易被愚弄。
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