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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.
"Human-level concept learning through probabilistic program induction" by Brenden M. Lake, Ruslan Salakhutdinov, and Joshua B. Tenenbaum has been published in the Dec. 11, 2015 issue of Science.
Washington Post Image
"For the first time we think we have a machine system that can learn a large class of visual concepts in ways that are hard to distinguish from human learners," said Joshua Tenenbaum
NIPS 2015
Prof. Joshua Tenenbaum (CBMM Research Thrust Leader) and Tejas Kulkarni (CBMM Siemens Graduate Fellow) are helping to organize a workshop for NIPS 2015, the Workshop on "Black Box Learning and Inference". Abstract submission deadline: Oct. 2, 2015
NIPS 2015 logo
Prof. Sam Gershman (CBMM, Harvard) and Prof Noah Goodman (CBMM, Stanford) are helping organize this workshop. Abstract submission deadline: Oct. 28, 2015
Prof. Mark J. Schnitzer (Stanford) presented on Thursday Nov. 13 2015, in the Singleton Auditorium, MIT Bldg 46.
Photo of  2016 Breakthrough Prize  recipients.
Prof Boyden was honored in recognition of his scientific research, specificaly for “transformative advances toward understanding living systems and extending human life.”
Photo of Prof. Ed Boyden
The award recognizes the outstanding achievements and contributions by a young neuroscientist who has recently received his or her advanced professional degree. The award will be presented during Neuroscience 2015, SfN’s annual meeting.
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MIT news featured a new machine learning project by CBMM members and affiliates, including Charlie Fogner, Chiyuan Zhang, Tomaso Poggio, Hossein Mobahi, and Mauricio Araya-Polo.

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