What are "traditional nets" ? What are the "other learning algorithms" ? What is a universal algorithm (and for what)? Neural nets are universal function approximators. There isnt something [edit: a function] they can't learn. When stacked they seem to produce results that are eerily human-like.
I think the "universal algorithm" in the article refers to some kind of emergent intelligence. Well, nothing that he mentions precludes it. Our brains aren't magical machines. Neural nets may not model real neurons, yet it is amazing how they can produce results that we identify as similar to the way we think. There is nothing in computational neuroscience that comes close to this. If anything, the success of deep nets bolsters my belief in connectionism rather than the opposite. I would expect it is very difficult to formulate "intelligence" mathematically, and to prove that DNs can or cannot produce it.
I think the "universal algorithm" in the article refers to some kind of emergent intelligence. Well, nothing that he mentions precludes it. Our brains aren't magical machines. Neural nets may not model real neurons, yet it is amazing how they can produce results that we identify as similar to the way we think. There is nothing in computational neuroscience that comes close to this. If anything, the success of deep nets bolsters my belief in connectionism rather than the opposite. I would expect it is very difficult to formulate "intelligence" mathematically, and to prove that DNs can or cannot produce it.