Big data and fast computing have advanced both neuroscience and artificial intelligence. The use of machine learning to compute vast amounts of brain data allows researchers to start reading out the mind and to predict behavior. In turn, the enormous power and efficiency of brain computing and cognition can inform artificial intelligence. For visual recognition tasks, brain-inspired deep learning algorithms now achieve near human-like performance. The marriage of brain science and machine learning will make both more useful for improving people’s lives.
Marvin Chun leads a cognitive neuroscience laboratory that uses brain imaging and machine learning to study how people see, attend, remember, and perform optimally. One line of work uses brain imaging to read out perceptions and thoughts. From brain scans, another project reveals and predicts what makes people different. He received his Ph.D. from MIT and his postdoctoral training at Harvard University. His research has been honored with several early-mid career awards, such as the Troland Research Award from the United States National Academy of Sciences, and the American Psychological Association Distinguished Scientific Award for an Early Career Contribution to Psychology. His undergraduate teaching of Introduction to Psychology, one of the largest classes in Yale College, has been recognized with both the Phi Beta Kappa William Clyde DeVane Medal for Distinguished Scholarship and Teaching, and the Lex Hixon '63 Prize for Teaching Excellence. This talk was given at a TEDx event using the TED conference format but independently organized by a local community. Learn more at https://www.ted.com/tedx