Yes but they are calling it AI, it's not AI by the scientific definition of it.
It seems the preferred terms among researchers is machine learning and deep neural nets rather than AI.
From a NY Times article this week:
"Machine learning isn’t just one technique. It encompasses entire families of them, from “boosted decision trees,” which allow an algorithm to change the weighting it gives to each data point, to “random forests,” which average together many thousands of randomly generated decision trees. The sheer proliferation of different techniques, none of them obviously better than the others, can leave researchers flummoxed over which one to choose. Many of the most powerful are bafflingly opaque; others evade understanding because they involve an avalanche of statistical probability. It can be almost impossible to peek inside the box and see what, exactly, is happening."
And within machine learning, the further preferred term appears to be deep neural nets. From the same NY Time article this week:
"Deep neural nets.....are now the class of machine learning that seems most opaque. Just like old-fashioned neural nets, deep neural networks seek to draw a link between an input on one end (say, a picture from the internet) and an output on the other end (“This is a picture of a dog”). And just like those older neural nets, they consume all the examples you might give them, forming their own webs of inference that can then be applied to pictures they’ve never seen before. Deep neural nets remain a hotbed of research because they have produced some of the most breathtaking technological accomplishments of the last decade, from learning how to translate words with better-than-human accuracy to learning how to drive."
Yes, the last application: learning how to drive. So deep neural nets are actually teaching themselves, which is its so called "black box."
I have read that Google engineers have spent several years creating news ways to visualise the inner workings of deep neural networks!
.