What a little more computing power can do for Deep Learning by Kim Martineau via @MIT

A deep learning model may need to see millions of photos before it can successfully identify a cat. The process is computationally intensive. But there may be a more efficient way - new MIT research shows that models only a fraction of the size are necessary.

An interesting viewpoint which could help to save money and time when developing this kind of model.