Deep Learning 2016: The Year in Review

http://www.deeplearningweekly.com/blog/deep-learning-2016-the-year-in-review

✔️ #Unsupervised and #Reinforcement Learning
✔️ Deep Reinforcement Learning
✔️ #Generative Models
✔️ Continued Openness in AI development
✔️ Partnerships & Acquisitions
✔️ Hardware & Chips

(by Jan Bussieck on December 31, 2016)

In order to understand trends in the field, I find it helpful to think of developments in #deep_learning as being driven by three major frontiers that limit the success of #artificial_intelligence in general and deep learning in particular. Firstly, there is the available #computing power and #infrastructure, such as fast #GPUs, cloud services providers (have you checked out Amazon's new #EC2 P2 instance ?) and tools (#Tensorflow, #Torch, #Keras etc), secondly, there is the amount and quality of the training data and thirdly, the algorithms (#CNN, #LSTM, #SGD) using the training data and running on the hardware. Invariably behind every new development or advancement, lies an expansion of one of these frontiers.
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