Geoffrey Hinton is distinguished for his work on artificial neural nets, especially how they can be designed to learn without the aid of a human teacher. This may well be the start of autonomous intelligent brain-like machines. He has compared effects of brain damage with effects of losses in such a net, and found striking similarities with human impairment, such as for recognition of names and losses of categorisation. His work includes studies of mental imagery, and inventing puzzles for testing originality and creative intelligence.
Professional position
- Emeritus University Professor, Department of Computer Science, University of Toronto
Awards
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Royal Medal
For pioneering work on algorithms that learn distributed representations in artificial neural networks and their application to speech and vision, leading to a transformation of the international information technology industry.
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Nobel Prize in Physics
For foundational discoveries and inventions that enable machine learning with artificial neural networks.
