Such software has certain distinctively teleological features. It employs massive reiteration in order to learn from outcomes. Performance improvement thus tends to descend from the future. To learn, without supervision, is to acquire a sense for fortune. Winning prospects are explored, losing ones neglected. After trying things out – against themselves – a few million times, such systems have built instincts for what works. ‘Good’ and ‘bad’ have been auto-installed, though, of course, in a Nietzschean or fully-amoral sense. Whatever, through synthetic experience, has led to a good place, or in a good direction, it pursues. Bad stuff, it economizes on. So it wins.
Unsupervised learning works back from the end. It suggests that, ultimately, AI has to be pursued from out of its future, by itself. Thus it epitomizes the ineluctable.
For those inclined to be nervous, it’s scary how easy all this is. Super-intelligence, by real definition, is vastly easier than it has been thought to be. Once the technological cascade is in process, subtraction of difficulty is almost the whole of it. Rigorously eliminating everything we think we know about it is the way it’s done.