[amiramir]

>How long until the next big idea? The last "AI winter", after expert systems, was 15 years.

Oddly enough neural nets languished in the frozen tundra for 50+ years if you take it back to perceptrons (mid 60's)[1]. Misnky and Papert's take down of perceptrons set the field back years. If you want to be more strict then it's been 31 years since Rummelhart and McClelland published their book[2], based on their earlier work that Hinton co-authored. They laid out multilayer NN with back-propagation. I got hold of the book in the UK in '87 and used it to code a multi-layer back-propagation network. It was a machine that would read out aloud given some text, even for words it had not seen before (good luck with through, though, and trough.) The problems were data and processing speed. I had to hand code features and wait for overnight training runs on VAXen and later a Sun-3 clocked at 16.67MHz[3]. It took big data an brute force to get the glimpses or magic that we see now. The fundamentals have been around for a long time.

It may be the case that one of the many approaches that fell by the wayside will make a comeback a al NN. NN added more layers and tweaked backprop, plus data and speed. It may be the expert systems will rejuvenate as something "new" with machines writing their own rules and somehow getting over showstoppers like the unmanageability of a large rule bases. It's probably going to be some combination of things that we already know about, along with yet more data, and processing power that will get us to the next level. The odds are that whatever that beast is will be self-training and regulating in an analogous way to back-prop but with logic thrown in. Good luck to us all for inventing such things, and for trying to understand what they are really doing.

[1]https://en.wikipedia.org/wiki/Perceptron [2]https://mitpress.mit.edu/books/parallel-distributed-processi... [3]https://en.wikipedia.org/wiki/Sun-3