Shortcomings of Deep Learning

Current Deep Learning successes such as AlphaGo rely on massive amount of labeled data, which is easy to get in games, but often hard in other contexts. You can’t play 20 questions with nature and win! By Oren Etzioni, CEO of the Allen AI, Founder of Farecast, Professor at UW, CSE Deep Learning has been incredibly successful in recent years, but it is still merely a tool for classifying items into categories (or for nonlinear regression).We have seen outstanding results in mapping images, audio segments, even board positions, into categories with ever-increasing accuracy, but AI needs to go way beyond classification and regression.Let’s talk about AlphaGo, which is a phenomenal technical achievement by the team at DeepMind.Yet, the overblown claims about the impressive success of AlphaGo are a case of…

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