Comment Re:Deep Learning (Score 4, Interesting) 152
I may be wrong but I believe all three (Watson, NEIL, and the cat thingy) are based on the same general "learning algorithm" (neural networks, specifically RBM's). What they do is find patterns in data, both the entities (atomic and compound) and the relationships. The "training" comes in two types, feeding it specific facts to correct a "misconception" it has formed, labelling the entities and relationship it found so a human can make sense of it.
What the cat project did was train a neural net to recognise a generic cat by showing it pictures of cats and pictures of non cats. It could then categorise random pictures as either cat or not-cat, until fairly recently the problem has always been - How do I train the same AI to recognise (say) dogs without destroying it's existing ability to recognise cats.
Disclaimer: I knew the math of neural nets well enough 20yrs ago to have passed a CS exam. I never really understood it in the way a I understand (say) geometry but I know enough about AI and it's ever shifting goal posts to be very impressed by Watson's Jeopardy stunt. To convincingly beat humans at a game of general knowledge really is a stunning technological milestone that will be remembered long after 911 goes back to being just a phone number.