AI Learns Things That Humans Didn't Teach It

Machine learning technology in neural networks has been pushing artificial intelligence (AI) development to new heights. Most AI systems learn to do things using a set of labelled data provided by their human programmers. Parham Aarabi and Wenzhi Guo, engineers from the University of Toronto, Canada have taken machine learning to a different level, developing an algorithm that can learn things on its own, going beyond its training. In a study published in the journal IEEE Transactions on Neural Networks and Learning Systems, the researchers discuss how they created an algorithm that identifies people's hair in photographs. Instead of the usual method of training neural networks (exposure to existing sets of examples), their algorithm learned directly from human instructions, a model called "heuristic training."