Sublime

learning with one another.

The intelligent machine must learn via observation of its world, including input from an instructor when necessary.

He was a wonderful educator, and he always told us to question assumptions. “There’s an assumption,” he said, “that schools are for students’ learning. Well, why aren’t they just as much for teachers’ learning?”

Hans Moravec has observed, “It is comparatively easy to make computers exhibit adult-level performance on intelligence tests or playing checkers, and difficult or impossible to give them the skills of a one-year-old when it comes to perception and mobility.”

But Herbert Simon, a cautious student of these matters, has said that “Insofar as we understand what processes are involved in human creativity—and we are beginning to have a very good understanding of them -none of the processes involved in human creativity appear to lie beyond the reach of computers.”

Over repetitive training sessions, our intelligent machine will build a model of its world as seen through its senses.

The understanding of learning must be genetic. It must refer to the genesis of knowledge. What an individual can learn, and how he learns it, depends on what models he has available. This raises, recursively, the question of how he learned these models. Thus the “laws of learning” must be about how intellectual structures grow out of one another an

and work by.

COMPLEX COGNITIVE CREATURES AREN’T BLANK SLATES.