From drugs to galaxy hunting, AI is elbowing its way into boffins' labs

Re: Machine Learning is not AI.

Correct.

It is barely even Maths.

You are correct insofar as the basic neural network techniques underlying "deep learning" have been around since at least the 80s (when they were already over-hyped in some quarters), if not earlier. What has changed is simply computing power and availability of huge data sets. I don't believe neural network-based machine learning was that widely deployed in earnest in the past, because it wasn't particularly effective given computing/data capacity at the time. That has changed, and it seems to me that neural networks in machine learning are indeed beginning to fulfil their early promise.

I do agree that the hype is irritating, and that broader appreciation of the history behind the techniques would be nice to see; but trashing a promising technology on whatever grounds doesn't seem particularly helpful either.

As for the ongoing "but machine learning isn't AI" whinge... fine, if someone can tell me what "real AI" is suppose to look like (actually no, really, please don't do that!) My suspicion is that machine learning, "deep learning", whatever, will turn out to be a building block on the road to more sophisticated machine intelligence, rather than a done deal. Meantime, if it's useful let's use it.

Re: GAN?

GAN does use the real data - that's the whole point: "The system is fed an input of images and the generator tries to recreate the pictures, while the discriminator tries to distinguish if the computer-made images are real or generated." It is being used to clean up degraded images: "Pairs of galaxy images are used during training. One image is high quality, and the other is degraded by blurring the image and adding noise to it." As such, it is as valid as other techniques such as the "traditional deconvolution methods" mentioned in the article, and which it apparently outperforms..