Continuous progress in artificial intelligence (AI) is raising expectations to build systems that learn and think like people. Many advances have come from using deep neural networks trained in tasks such as object recognition, language translation or board games.
Despite their biological inspiration and performance achievements, these systems differ from human intelligence in crucial ways.
One source of inspiration to advance AI to a level closer to human thinking comes from Geoffrey Hinton, Professor at the University of Toronto and a Google researcher. Another comes from Joshua Tenenbaum, Professor at MIT’s Department of Brain and Cognitive Sciences, engaged in reverse engineering the human mind.MORE COMMENT