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I Am Excited About The Big Picture

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Hi Song,

I am really excited about the high ambition you are setting in for the team by aiming at expanding AI ventures toward multiple directions.

I gave further thought on the big picture. I have some application ideas in mind. But first, I would like to describe the core idea that would underlie all the application and its innovative advantage, especially in comparison to other AI groups.

The main and unique idea that we will bring in is the representation of knowledge regarding general predictions. It is beyond the current trend toward end-to-end training that stays agnostic about how knowledge is presented. Instead of blind compositionality through deep layers, we are interested in deep layers meaningful questions, each of which can then be learned using the current deep-learning machinery. Slowly, the AI community is also paying attention to prediction, but their approach is limited in several important ways:

1) In reinforcement learning, we have a powerful way of formulating semantically powerful, scalable and grounded predictive questions. In conventional AI applications, questions are always about short-term fixed-time horizon sensory events. Predictive questions in reinforcement learning can be about sensory events that occur in an indefinite horizon. The policy of the agent is almost always unspecified or implicitly specified, obscuring the meaning of predictions. On the other hand, policies are always explicitly specified in reinforcement learning, allowing

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