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Why Deep Language Understanding (NLP) cannot be solved as easily as image recognition, but there is hope

The second AI winter came to a sudden finale in 2012 when AlexNet took first prize in the ImageNet competition. Deep learning was born.

Yet, it took many more years before similar deep learning techniques were effectively applied to language. Words and characters, surely, can’t be as complex to interpret as images or pixels which consume thousands of times more memory? Au contraire, language is a much more complex problem than vision.

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