Today's AI is, as I like to call it, statistics with sexy marketing. A lot of AI programming consists of loading Python modules that correspond to various models, and fooling around with them to see which best fits the data you have. In other words, you're working more like a mathematician experimenting with potential solutions.
There's pressure at my job for architects to "leverage AI". What I always suggest to them is to find a statistician and see if things like neural networks are even necessary before committing to them. Sometimes the problem could best be solved with a heuristic, a rules engine, or a simple statistical model like linear regression, in which case "leveraging AI" is merely hype.
There's pressure at my job for architects to "leverage AI". What I always suggest to them is to find a statistician and see if things like neural networks are even necessary before committing to them. Sometimes the problem could best be solved with a heuristic, a rules engine, or a simple statistical model like linear regression, in which case "leveraging AI" is merely hype.