Machines that learn language more like kids do
Computer model could improve human-machine interaction, provide insight into how children learn language.
Computer model could improve human-machine interaction, provide insight into how children learn language.
Technique from MIT could lead to tiny, self-powered devices for environmental, industrial, or medical monitoring.
Program users can tinker with landing and path planning scenarios to identify optimal landing sites for Mars rovers.
Machine learning system efficiently recognizes activities by observing how objects change in only a few key frames.
Breakthrough CSAIL system suggests robots could one day be able to see well enough to be useful in people’s homes and offices.
Personalized machine-learning models capture subtle variations in facial expressions to better gauge how we feel.
Made of electronic circuits coupled to minute particles, the devices could flow through intestines or pipelines to detect problems.
Improved design may be used for exploring disaster zones and other dangerous or inaccessible environments.
Spyce, a robot-assisted restaurant located in Boston, was invented to respond to a common MIT student desire: good, low-cost food.
Machine learning network offers personalized estimates of children’s behavior.
Low-power design will allow devices as small as a honeybee to determine their location while flying.
Computer Science and Artificial Intelligence Laboratory system enables people to correct robot mistakes on multiple-choice tasks.
New printing technique could be used to develop remotely controlled biomedical devices.
PhD candidate and Amazon Robotics Challenge winner Maria Bauza helps to improve how robots interact with the world.
Mechanical engineering researchers are using AI and machine learning technologies to enhance the products we use in everyday life.