[jacquesm]

That's got to be one of the most concise but still complete descriptions of deep learning that I've seen so far.

The question that it implicitly raises (at least, with me) is how can we tell the difference between 'understanding' and 'deep learning' if the end results are the same?

To me 'reasoning' is a slow, conscious process, and understanding is a part of that. But classification problems , especially when done by humans when they try to work fast have no room for such conscious decision making, we go much faster than that and outsource the job to our subconscious. Predictably, the error rate goes up and in those kind of situations deep learning can today already outperform humans on the same tasks.

The weird thing is that deep learning solutions can get simple cases completely wrong, where a human would never err, and yet get some of the hardest cases - where a human would be very likely to make an error - right. It's baffling.