Yesterday I wrote how AI made big promises in the past but it failed to deliver, but that now it’s different, because of machine learning.
Well, now we have several products that work well with machine learning. My favorite example is Google Photos, Synology Moments and PhotoPrism. They are all photo management applications which use machine learning to automatically recognize all faces in pictures (easy, we had this for 15 years), recognize automatically which pictures are of the same person (hard, but doable by hand if you had too much time) and more than that, index photos by all kinds of objects that are found in them, so that you can search by what items appear in your photos (really hard, nobody had time to do that manually).
I have more than 10 years of photos uploaded to my Synology and one of my favorite party tricks when talking to someone is to whip out my phone and show them all the photos I have of them, since they were kids, or the last time that we met, or that funny thing that happened to them and I have photographic evidence of. Everyone is amazed by that (and some are horrified and deny that they looked like that when they were children). And there is not one, but at least three options to do this, one of which is open source, so that anyone can run in at home on their computer, for free, so there is demand for such a product.
Other successful examples are in the domain of recommender systems, YouTube being a good example. I have a love/hate relationship with it: on one hand, I wasted so many hours of my life to the recommendations it makes (which is proof of how good it is at making personalized suggestions), on the other hand, I found plenty of cool videos with it. This deep learning based recommender system is one of the factors behind the growth of the watch time on YouTube, which is basically the key metric behind revenue (more watch time, more ads).
These are just two examples that are available for everyone to use, and which serve as evidence that machine learning based AI now is not just hot air.
But I still haven’t answered the question what is ML… tomorrow, I promise.