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DeepMind is the name of an AI company that was acquired by Google.

AlphaGo is the program that beat Go. These game playing algorithms are variations of Deep Q Learning Reinforcement Learning algos.

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And here's the related paper, "Unifying Count-Based Exploration and Intrinsic Motivation": https://arxiv.org/abs/1606.01868

Tech journalism isn't at its best when it can't distinguish between WOPR and a team of researchers.

DeepMind's main intellectual property, the reason why it was acquired, was DeepMind's reinforcement algorithm. The present paper, like the work on AlphaGo, is about improving this reinforcement algorithm.

I don't believe that's the case. The Atari results were achieved via Q-Learning with neural networks (DQN stands for Deep Q-Networks), both of which have been around for decades. The basic algorithm is something you can implement yourself fairly easily, but (as with most things involving neural nets) getting it to really perform takes a bit of expertise.

So, DeepMind's greatest asset is they employ some really excellent people and have a substantial head start in terms of actually implementing AIs and getting them to work.

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