Don't fall for the AI hype: Here are the ingredients you need to build an actual useful thing


Artificial intelligence these days is sold as if it were a magic trick. Data is fed into a neural net – or black box – as a stream of jumbled numbers, and voilà! It comes out the other side completely transformed, like a rabbit pulled from a hat. That's possible in a lab, or even on a personal dev machine, with carefully cleaned and tuned data. However, it is takes a lot, an awful lot, of effort to scale machine-learning algorithms up to something resembling a multiuser service – something useful, in other words.