Josh Tenenbaum receives 2019 MacArthur Fellowship
Brain and cognitive sciences professor studies how the human mind is able to learn so rapidly.
Brain and cognitive sciences professor studies how the human mind is able to learn so rapidly.
How people interpret musical notes depends on the types of music they have listened to, researchers find.
Study reveals brain regions that respond differently to the presence of background noise, suggesting the brain progressively hones in on and isolates sounds.
Researchers combine deep learning and symbolic reasoning for a more flexible way of teaching computers to program.
Study shows that artificial neural networks can be used to drive brain activity.
The DiCarlo lab finds that a recurrent architecture helps both artificial intelligence and our brains to better identify objects.
Professor honored for work on the nature and origins of intelligence in the human mind and applying that knowledge to build human-like intelligence in machines.
Computer model could improve human-machine interaction, provide insight into how children learn language.
New investment supports intelligence research, student fellowships.
In simulations, robots move through new environments by exploring, observing, and drawing from learned experiences.
Advances in computer vision inspired by human physiological and anatomical constraints are improving pattern completion in machines.
Faculty from across the Institute tapped to lead new initiative in human and machine intelligence.
Results may help explain how humans do the same thing.
Ten-month-old infants determine the value of a goal from how hard someone works to achieve it.
Before assigning responsibility, our minds simulate alternative outcomes, study shows.