The regression mentioned in the press release was only used to predict one property (the Curie temperature) of the materials based on experimental data for similar materials.
It's still a really impressive piece of work, just nothing to do with AI.
The paper is open access, so you can read the full text here: http://advances.sciencemag.org/content/3/4/e1602241.full
They spot facts in byte streams that we don't see. We can then contextualize the info into another part of the domain, or drive it deeper.
Ask a convolutional neural network what "cat" means, and the best you can get is a probability distribution of pixels on a grid. It's not intelligence, but just an encoding of facts provided by an actual intelligence.
Once they stop tweaking Watson (example) for every tasks, I'll declare it an AI.
... via my fortune clone @ https://github.com/globalcitizen/taoup
From what I understand, we already have; that's why you usually see it called "machine learning" in research and academia - and "artificial intelligence" everywhere else.
That isn't to say there's no crossover in both directions, but usually if you are being serious on the subject, you call it ML - if you're trying to hype it or build interest, you call it AI.
Note that this only goes back so far; prior to the early 2000s or so, the terms were used more or less interchangeably. At one point, the term "machine intelligence" was used, then died out, but I've seen it used again recently.