Image for NIPS 2015 Workshop on Black Box Learning and Inference
December 12, 2015 - 8:30 am
Prof. Joshua Tenenbaum (CBMM Research Thrust Leader) and Tejas Kulkarni (CBMM Siemens Graduate Fellow) are helping to organize the NIPS 2015 Workshop on Black Box Learning and Inference.
 
Overview
Probabilistic models have traditionally co-evolved with tailored algorithms for efficient learning...
Image from NYT Dec 11, 2015
December 11, 2015 - 9:45 am
The recent Science paper, "Human-level concept learning through probabilistic program induction" by Prof. Tenenbaum, Brenden M. Lake and Ruslan Salakhutdinov, has received press coverage from the New York Times. Excerpt from the New York Times: "Computer researchers reported artificial-intelligence advances on Thursday that surpassed human capabilities for a narrow set of vision-related tasks. The improvements are noteworthy because so-called...
Cover image for the Dec. 11, 2015 issue of Science
December 11, 2015 - 9:30 am
"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. Their work was also selected for the cover image. Abstract: People learning new concepts can often generalize successfully from just a single example, yet machine learning algorithms typically require tens or hundreds of examples to perform with similar...
Nips
December 11, 2015 - 8:30 am
Prof. Sam Gershman (CBMM, Harvard) and Prof Noah Goodman (CBMM, Stanford)
We are pleased to announce a NIPS workshop on Bounded Optimality and Rational Metareasoning, which will take place on December 11, 2015, in Montreal, Canada.
This workshop brings together computer scientists working on...
Image by Danqing Wang (The Washington Post)
December 10, 2015 - 4:00 pm
by Joel Achenbach The Washington Post December 10, 2015 An excerpt from the article: "Machines and humans learn differently. This has been a central fact of Artificial Intelligence research for decades. If you cram enough data into a machine, and let the algorithms grind away tirelessly, the computer can detect a pattern, produce a desired outcome and perhaps beat a grandmaster in chess. Human intelligence is faster, quirkier and more nimble. We...
Figure from New York Times article.
December 10, 2015 - 4:00 pm
By John Markoff Dec. 10, 2015 Excerpt: "Computer researchers reported artificial-intelligence advances on Thursday that surpassed human capabilities for a narrow set of vision-related tasks. The improvements are noteworthy because so-called machine-vision systems are becoming commonplace in many aspects of life, including car-safety systems that detect pedestrians and bicyclists, as well as in video game controls, Internet search and factory...
Logo for NIPS 2015 Symposium: Brains, Minds and Machines
December 10, 2015 - 3:00 pm
 
If you are more interested in the engineering of tomorrow -- and the science of today -- rather than in today's engineering practices....come to us!
The Center for Brains, Minds and Machines (CBMM) will be coordinating one of the three symposia at the 29th Annual Conference on Neural Information...
Image: Jose-Luis Olivares/MIT
December 10, 2015 - 12:00 pm
Larry Hardesty | MIT News Office December 10, 2015   Excerpt from the article: "Researchers at MIT, New York University, and the University of Toronto have developed a computer system whose ability to produce a variation of a character in an unfamiliar writing system, on the first try, is indistinguishable from that of humans. ... “In the current AI landscape, there’s been a lot of focus on classifying patterns,” says Josh Tenenbaum, a professor...
CBMM logo
December 2, 2015 - 4:30 pm
Shimon Ullman, Boris Katz
Thrust 3 Projects
Yevgeni Berzak - Human Language Learning
Abstract: Linguists and psychologists have long been studying cross-linguistic transfer, the influence of native language properties on linguistic performance in a foreign language. In this work we provide empirical evidence for this...
December 2, 2015 - 3:30 pm
Topic: "Measuring object detection performance at scale in humans and machines" (cont.)
Wed. Dec. 02, 2015, 3:30 pm - 4:30 pm
Location: Harvard, NW-255
Brainstorming on the limitations of tasks and evaluations regarding object detection. The topic is very relevant to CBMM and the hope is to have a ...
CBMM logo
November 18, 2015 - 4:00 pm
Sam Gershman  
Abstract: Reinforcement learning is typically conceived of in terms of how reward predictions and choice behavior adapt based on an agent's experience. However, experience is too limited to provide the brain with the knowledge necessary for adaptive behavior in the real world. To go beyond...
Photo of Marine Biological Laboratory (MBL)  viewed from Eel Pond
November 16, 2015 - 9:00 am
Marine Biological Laboratory (MBL) is now accepting application s for the  Summer 2016 Advanced Research Courses. Advanced Research Courses include the CBMM organized Brains, Minds and Machines course, which will run from August 15, 2016 to September 5, 2016, at Woods Hole, MA.   Brains, Minds and Machines Course Date: August 15 – September 5, 2016Location: Marine Biological Laboratory (MBL), Woods Hole, MA.Directors: Gabriel Kreiman, Harvard...
Photo of Prof. Mark J. Schnitzer
November 13, 2015 - 4:00 pm
Mark J. Schnitzer
Prof. Mark J. Schnitzer, Departments of Biology and Applied Physics, Howard Hughes Medical Institute, Stanford University
Abstract: A longstanding challenge in neuroscience is to understand how the dynamics of large populations of individual neurons contribute to animal behavior and brain disease....
Winners of the 2016 Breakthrough Prize awards in Mountain View, Calif., on Sunday evening. Credit Steve Jennings/Getty Images
November 9, 2015 - 6:45 pm
Congratulations to Prof. Edward Boyden who was one of five scientists presented with the Breakthrough Prize in Life Sciences last night. Prof Boyden was honored in recognition of his scientific research, specificaly for “transformative advances toward understanding living systems and extending human life.”   The Breakthrough Prize in Life Sciences honors transformative advances toward understanding living systems and extending human life. The...

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