Why NOW is the best time to get into neural networks

(1) No more mystery. The ("initially cloaked in a veil of mysterious superpowers") AlexNet of 2012 that became such a frequent topic of conversation and citation has since been superseded by a plethora of new architectures, each offering an exploration of a new setting of parameters or architectural choices. One can now skip the initial phase of questioning and wonderment (of why the network works so well and how each architectural choice contributes), throw off the veil of mystery, and read about what we now know about neural network architectures in general, after trying a bunch.

(2) Make-your-own psychedelic pictures. After deep dream debuted, the number of people who wanted to create a psychedelic picture for their Facebook profiles skyrocketed, resulting in a surge of caffe downloads, installation and compilation headaches, forum discussions, online tutorials, and subsequent caffe improvements. Pretty much every problem or error that could occur has been logged somewhere on the web via what has become massive, crowd-sourced QA (and I'm not even mentioning all the other possible libraries). You may now proceed.

(3) In the news. The terms "neural networks" and "deep learning" have escaped the ivory towers of academia and have appeared in all forms of media. They continue to trickle down from the more specialized channels to reach increasingly broader audiences. From introductory talks at (non-CS) conferences about the potential power of neural networks, to Google I/O 2015 announcements about the reliance on neural net technology to increasingly power applications, to endless tech news and feature articles about neural networks (and the future), to even appearing in Silicon Valley... now if Homer Simpson next utters the words 'neural networks' but they are not in your casual, day-to-day vocabulary, then shame on you.

(4) Spoon-fed brilliance. Brilliant people have taken the time to digest and curate a whole load of content for the rest of us. Some examples: lecture notes and tutorials, textbooks, summer schools; and online courses. Those same brilliant people answer tons of questions on forums and social networks (e.g. recurring Q&A sessions on Quora). One of the hundreds of available explanations/expositions of neural networks will surely speak to you.

(5) A glimpse of the future. No doubt we are all heading towards more advanced systems, backed my neural network architectures. Large companies are rushing to build bigger, faster, more robust deep learning software and hardware, small start-ups with neural network backing are springing up all over the place, and just about every field (from healthcare to organic chemistry to social science) is beginning to feel this tidal wave on the horizon. Should at least know about what's going to hit you.

and the list goes on...