Deep learning architectures built by machines (so we no longer have to design architecture to solve problems) https://arxiv.org/abs/1611.01578 Transfer Learning (so we need less data to build models) http://ftp.cs.wisc.edu/machine-learning/shavlik-group/torrey... Generative adversarial networks (so computers can get human like abilities at generating content) https://papers.nips.cc/paper/5423-generative-adversarial-n…
>> Generative adversarial networks (so computers can get human like abilities at generating content) Does this only apply to artistic content, or also to engineering content ? Say PCB layouts, architectural plans, mechanical designs, etc ?
[edit]: it is a lot harder to build a NN when there are very constraint rules. But it is also a lot easier to verify and penalize it and generate synthetic data.