[freehunter]

>maybe I'm one of few doing AI projects not involving a deep neural net

You're not. While progress in machine learning is astounding and is going to do great things for humanity, it is kind of frustrating that "AI" to many people these days means neural nets, deep learning, high-end GPUs, and huge datasets. Not every problem needs machine learning as a solution, and there are still some of us solving hard problems with classical AI and old fashioned data analysis. But it's not trendy right now.

[solarkraft]

What kinds of problems are best solved by AI, but not deep learning/neural nets?

[freehunter]

Natural language processing is a big area where classical AI is heavily used and machine learning is lagging behind. ML is terrible at teaching computers to read and/or produce human writing. Compare what the company Automated Insights is doing for news articles versus neural networks writing books and movie scripts (with humorous results).

Anything with a known and well-defined set of rules can also be programmed more efficiently with decision trees/Markov chain than through machine learning. There's no need to use tons of data to train a model to do something over time when all it needs is the rule book.

Machine learning is basically advanced pattern matching, neural nets often require you to brute force the problem with tons of data. There are plenty of places where you're not matching patterns and you don't have tons of data but the computer still needs to make a decision after analyzing the data that is available.