The effort to discern a “better” humanity continues with the search for a more learning-efficient artificial intelligence. The use of probability provides dramatic efficiency gains in robotic learning.
“What’s brilliant about this is that it allows you to build a cognitive model in a fantastically much more straightforward and transparent way than you could do before,” says Nick Chater, a professor of cognitive and decision sciences at University College London. “You can imagine all the things that a human knows, and trying to list those would just be an endless task, and it might even be an infinite task. But the magic trick is saying, ‘No, no, just tell me a few things,’ and then the brain — or in this case the Church system, hopefully somewhat analogous to the way the mind does it — can churn out, using its probabilistic calculation, all the consequences and inferences. And also, when you give the system new information, it can figure out the consequences of that.”
