Home Page Spotlights
This course explores the problem of intelligence-its nature, how it is produced by the brain and how it could be replicated in machines—using an approach that integrates cognitive science, neuroscience, computer science, and artificial intelligence.
“Ed’s body of work has already transformed neuroscience and biomedicine, and this chair will help his team to further develop revolutionary tools that will have a profound impact on research worldwide.” - Robert Desimone, Director McGovern Institute
The VSS Davida Teller Award was established in 2013 and is given to "an outstanding woman vision scientist with a strong history of mentoring."
On a quest to demystify deep learning, Tomaso Poggio glimpses tantalizing implications for human intelligence.
Award is in recognition of Prof. McDermott's "groundbreaking research into how humans hear and interpret sound." Award will be presented at the NAS's 155th Annual Meeting on April 29, 2018.
Dr. Hermundstad discussed how the central visual system, operating with different goals and under different constraints, makes efficient use of resources to extract meaningful features from complex visual stimuli.
At a time of rapid advances in intelligence research across many disciplines, this initiative will encourage researchers to investigate the societal implications of their work as they pursue hard problems lying beyond the current horizon of what is known.
CBMM is happy to announce that Yen-Ling Kuo has been named the CBMM Siemens Graduate Fellow. Yen-Ling is a PhD student in Computer Science and Artificial Intelligence Laboratory (CSAIL).
This course combines cognitive neuroscience, cognitive psychology, and artificial intelligence, and enables students to learn about thinking and science in ways that impact and inform their future studies and their daily lives.
In this talk, Jeff discussed a theory that sensory regions of the neocortex process two inputs: 1) the sensory data arriving via thalamic relay cells; and 2)Jeff will propose the second is a representation of allocentric location.
As part of an investigation into the nature of humans' physical intuitions, MIT researchers trained a neural network to predict how unstably stacked blocks would respond to the force of gravity.
A warm "Thank You!" to everyone for another wonderful year of exciting advances at the Center for Brains, Minds and Machines
In this talk, Prof. Müller discussed the topic of ML applications in the sciences, in particular in neuroscience, medicine and physics.
An intensive three-week course which gives a “deep end” introduction to the problem of intelligence.
Ten-month-old infants infer the value of goals from the costs of actions, Science, Nov. 2017