Dynamic Deep Learning

Dynamic Deep Learning: a paradigm shift in AI research and tools: AI research has seen many shifts in the last few years. We’ve seen research go from using static datasets such as Imagenet to being more dynamic and online in self-driving cars, robots and game-playing.Many dynamic environments such as Universe and Starcraft are being used in AI research to solve problems pertaining to reinforcement learning and online learning. In this talk, I shall discuss these shifts in research. Tools such as PyTorch, DyNet and Chainer have popped up to cope up with the paradigm shift, enabling cutting-edge AI, and I shall discuss these as well.

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