AI Learns Things That Humans Didn’t Teach It

A heuristic approach 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. This figure compares a traditionally trained algorithm to Aarabi and Guo’s heuristically trained neural net. The left and centre columns show an aggressive and conservative image-recognition algorithm trained to recognized human hair, compared to the more precise heuristically trained algorithm at right. Credit: Courtesy: IEEE Trans NN & LS In a study published in the journal IEEE Transactions on Neural Networks and…


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