If we define 'learning' in an appropriate way, then any good research library already knows "everything about anything". Okay, let the thing 'learn' about the

If we define 'learning' in an appropriate way, then any good research library already knows "everything about anything". Okay, let the thing 'learn' about the Kuhn-Tucker conditions by searching on Google and reading, say, Wikipedia or some books at Google or Amazon. Then have the thing show that for problems in functional form the Zangwill and Kuhn-Tucker constraint qualifications are independent. Do that and I will start to believe that the terminology 'deep learning' is appropriate. I'm not holding my breath. Yes, it may be that in some rough sense the kind of 'learning' it is doing is roughly like some of the learning of a child of, say, 2 as it is starting to learn about language and things. Yes, it may be that such 'learning' is a significant part of the intelligence of, say, a child of 3-5. Maybe. Big, huge maybe. When I was working in AI, I noticed the terminology had been cooked up to imply much more than was being accomplished. Now, as I understand it, there is a specific definition for the current AI term 'deep learning' and has to do with the 'depth' of where adjust parameters in a neural network, not how 'deep' the 'learning' is about the subject in question. Cute terminology.