The Center for Brains, Minds & Machines

DeepMind’s AI predicts structures for a vast trove of proteins [Nature]

AlphaFold neural network produced a ‘totally transformative’ database of more than 350,000 structures from Homo sapiens and 20 model organisms.
Highly accurate protein structure prediction with AlphaFold [Nature]

A new paper by DeepMind scientists and CBMM EAC Member Demis Hassabis on their solution to the 'protein folding problem' using their AI system Alphafold.
CBMM Annual Retreat 2021

The 2021 CBMM Annual Retreat and tentative schedule has been announced!
Scientists discover a new class of memory cells in the brain [EurekaAlert!]

Scientists have long searched in vain for a class of brain cells that could explain the visceral flash of recognition that we feel when we see a very familiar face, like that of our grandmothers. CBMM's Winfrich Friewald and colleagues have discovered...
Two decades of biology outreach [MIT Biology]

A lifelong interest in teaching brought CBMM's Mandana Sassanfar to MIT, where she has established programs to engage diverse students and forged partnerships with institutes across the country.
Brains, Minds + Machines Summer Course | MBL Woods Hole, MA

An intensive three-week course which gives a “deep end” introduction to the problem of 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

Stuart Russell and Tomaso Poggio

SPARKS! Podcast #1 Brainy AI — with Stuart Russell and Tomaso Poggio [CERN]

July 9, 2021

Do we need to understand the brain to make progress in artificial intelligence? In the first podcast in the series, Stuart Russell and Tomaso Poggio contrast “deep learning” with our own organic...

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Seminars + events

CBMM Annual Retreat

August 19, 2021 - 10:00 am

To be held remotely via Zoom Tentative agenda (pdf)

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CBMM spotlight

James Traer: Reverberation

James Traer: Reverberation

Associated Research Thrust(s):

Exploring Future Directions

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Highlighted publications

J. Jumper, Evans, R., Pritzel, A., Green, T., Figurnov, M., Ronneberger, O., Tunyasuvunakool, K., Bates, R., Žídek, A., Potapenko, A., Bridgland, A.,...

S. M. Landi, Viswanathan, P., Serene, S., and Freiwald, W. A., “A fast link between face perception and memory in the temporal pole”, Science, p. eab...

CBMM Memo No:

116

O. Kunhardt, Deza, A., and Poggio, T., “The Effects of Image Distribution and Task on Adversarial Robustness”. 2021.

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Featured video

Embedded thumbnail for Next-generation recurrent network models for cognitive neuroscience

Next-generation recurrent network models for cognitive neuroscience

Recurrent Neural Networks (RNNs) trained with machine learning techniques on cognitive tasks have become a widely accepted tool for neuroscientists. In comparison to traditional computational models...

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