Home Page Spotlights

RegML is an advanced machine learning course, scheduled for June 27, 2016 - July 1, 2016, Genoa, Italy. Application deadline April 15, 2016
Group photo of the 2015 CBMM Undergraduate Summer Research Interns
Watch the new video of the CBMM Undergraduate Summer Research Internships in Neuroscience
Google's AlphaGo defeats South Korean Go master Lee Sedol
Google's DeepMind group, and CBMM Industrial Partner, developed an artificial intelligence to master the traditional Chinese game "Go". In March, 2016, AlphaGo defeated South Korean Go master Lee Sedol in a best-out-of-five match.
Google DeepMind
Google and Korean Baduk (Chinese Go) Association (KBA) today held the “Google Deepmind Challenge Match Press Briefing” to announce the details on the upcoming Go games between Sedol Lee (9-dan) and AlphaGo, a computer AI by Google DeepMind.
Fig. S2 MIRCs coverage, Atoms of recognition in human and computer vision, Ullman, et al, PNAS 2016
Digital Baby Project's Aim: Computers That See Like Humans
Photo of Marvin Minsky with a toy robot in the foreground. Photo Credit Boston Globe
Marvin Minsky (1927–2016)
"On Wednesday, DeepMind, a research organization that operates under the umbrella of Alphabet, reported that a program combining two separate algorithms had soundly defeated a high-ranking professional Go player in a series of five matches."
Prof. Nancy Kanwisher presents to a packed Singleton Auditorium
On Friday, Jan. 15th, 2016, the Center for Brains, Minds & Machines hosted a day of talks displaying the collaboration and interaction between Neuroscientists and Computer Scientists at MIT. The largest auditorium in building 46 was packed with interest.
We have assembled a stellar list of speakers at the intersection of Neuroscience and AI from both sides of Vassar Street who will give an account of how this multi-disciplinary interaction affects their work.
Photo of a microscope.
Prof. Matt Wilson will be teaching an ethics course during MIT IAP 2016, see details included below. CBMM grad students and postdocs, who have not yet completed a similar ethics course, are encouraged to register.
Image: MIT News
Machines that learn like people Algorithms could learn to recognize objects from a few examples, not millions; may better model human cognition.
Illustration: Christine Daniloff/MIT
“Our findings are hard to reconcile with the idea that music piggybacks entirely on neural machinery that is optimized for other functions, because the neural responses we see are highly specific to music,” says Nancy Kanwisher.
Screenshot from video displaying 3D imaging of a brain.
Researchers from the Kanwisher and McDermott Labs discuss research which identified a neural population highly selective for music.
IMAGE-The New York Times 12/11/2015
“With all the progress in machine learning, it’s amazing what you can do with lots of data and faster computers,” said Joshua B. Tenenbaum.