The Center for Brains, Minds & Machines

The State of Autonomous Driving

On March 19, 2019, CBMM External Advisory Committee member and CBMM collaborator Dr. Amnon Shashua presented progress on autonomous driving and other AI based adaptive technologies.
The Power of Self-Learning Systems

On March 20, 2019, CBMM External Advisory Committee member and CBMM collaborator Dr. Demis Hassabis presented progress on self-learning systems work at Google DeepMind with examples from AlphaGo and AlphaStar.
The Science of Intelligence Learning Hub is now online!

Explore the science of intelligence through lectures, tutorials, and courses offered by the CBMM community, and experiment with modeling and data analysis tools used in neuroscience, cognitive science, and AI, to study intelligence in brains and machines!
Tomaso Poggio: Brains, Minds, and Machines (video/podcast) [Lex Fridman]

He is a professor at MIT and is the director of the Center for Brains, Minds, and Machines. Cited over 100,000 times, his work has had a profound impact on our understanding of intelligence, in both biological neural networks and artificial ones...
Brains, Minds + Machines Summer Course 2019 | MBL Woods Hole, MA

An intensive three-week course which will give a “deep end” introduction to the problem of intelligence. Course will be held from Aug. 8, 2019 through Aug. 29, 2019, at MBL, Woods Hole, MA, Application Deadline: April 8, 2019
The Brains, Minds and Machines Summer Course is now available on the MIT Open Course Ware website!

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.

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Videos | Support Us

The Center for Brains, Minds and Machines (CBMM)
is a multi-institutional NSF Science and Technology Center
dedicated to the study of intelligence - how the brain produces intelligent
behavior and how we may be able to replicate intelligence in machines.

The Center for Brains, Minds and Machines (CBMM) is a multi-institutional NSF Science and Technology Center dedicated to the study of intelligence - how the brain produces intelligent behavior and how we may be able to replicate intelligence in machines.

Summer course students working / Marine Biology Lab, Woodshole, MA

Brains, Minds, and Machines Summer Course

A CBMM flagship program, the Brains, Minds, and Machines Summer Course is an immersive 3-week course that provides a broad introduction to research on human & machine intelligence, combining three core disciplines — computation, neuroscience, and cognition — where students learn about common empirical & theoretical methods used in the field, and compelling results of this research, with an emphasis on the scientific mission of the Center.read more »

Prof. Nancy Kanwisher lecturing to a room full of students

The Science of Intelligence Learning Hub

Explore the science of intelligence through lectures, tutorials, and courses offered by the CBMM community, and experiment with modeling and data analysis tools used in neuroscience, cognitive science, and AI, to study intelligence in brains and machines!read more »

Featured news

IMAGE: This figure shows natural images (right) and images evolved by neurons in the inferotemporal cortex of a monkey (left). Credit: Ponce, Xiao, and Schade et al./Cell

These trippy images were designed by AI to super-stimulate monkey neurons [EurekAlert!]

May 2, 2019

To find out which sights specific neurons in monkeys "like" best, researchers designed an algorithm, called XDREAM, that generated images that made neurons fire more than any natural images the...

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Seminars + events

Research Meeting: Katharina Dobbs (Kanwisher, Module 3)

June 11, 2019 - 4:00 pm

Katharina Dobbs

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CBMM spotlight

Candace Ross: Artificial Learning

Candace Ross: Artificial Learning

Associated Research Thrust(s):

Vision and Language

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Highlighted publications

C. R. Ponce, Xiao, W., Schade, P. F., Hartmann, T. S., Kreiman, G., and Livingstone, M. S., “Evolving Images for Visual Neurons Using a Deep Generati...

P. Bashivan, Kar, K., and DiCarlo, J. J., “Neural Population Control via Deep Image Synthesis”, Science, vol. 364, no. 6439, 2019.

K. Kar, Kubilius, J., Schmidt, K., Issa, E. B., and DiCarlo, J. J., “Evidence that recurrent circuits are critical to the ventral stream’s execution...

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Featured video

Embedded thumbnail for [video] Evolving Images for Visual Neurons Using a Deep Generative Network Reveals Coding Principles and Neuronal Preferences

[video] Evolving Images for Visual Neurons Using a Deep Generative Network Reveals Coding Principles and Neuronal Preferences

Five authors of the above paper, published in the journal "Cell", describe their methods and findings on exciting neurons using generative neural networks in real time.

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