The Center for Brains, Minds & Machines

CBMM welcomes Guangyu Robert Yang

Please help us welcome our newest Investigator Guangyu Robert Yang - who will be arriving at the MIT campus in July - coming from the Center for Theoretical Neuroscience of Columbia University.
Josh McDermott seeks to replicate the human auditory system

Computer models that mimic humans’ extraordinary hearing abilities could improve treatments for hearing loss. MIT neuroscientist Josh McDermott hopes to develop computational models that can perform sophisticated auditory tasks as well as the human brain.
Tomaso Poggio to speak at the Bower Award Webinar

Prof. Poggio will give a talk at the Bower Award for Neural Networks for Machine Learning symposium honoring Kunihiko Fukushima on April 28, 2021 at 9:00AM ET. Click to see full list of speakers and register for the webinar.
Memory as a cornerstone of intelligence

Memory permits the reuse of past cognitive computations. Work by CBMM's Dasgupta and Gershman have suggested that memory may be much more ubiquitous, permeating many other computational systems.
"Biological and Computer Vision" by Gabriel Kreiman

This new book introduces the neuroscientific study of neuronal computations in visual cortex alongside of the psychological understanding of visual cognition and the burgeoning field of biologically-inspired artificial intelligence.
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

ISSNAF Young Investigator Awards 2021 Call

June 9, 2021

ISSNAF, the Italian Scientists and Scholars in North America Foundation, annually awards the Young Investigator Awards in various disciplines to outstanding, early-career Italian researchers...

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Seminars + events

Photo of Guangyu Robert Yang, MIT

CBMM Special Seminar: Next-generation recurrent network models for cognitive neu...

June 15, 2021 - 2:00 pm

This seminar talk will be hosted remotely via Zoom.

Guangyu Robert Yang, Dept. of Brain and Cognitive Sciences (...

Abstract: Recurrent Neural Networks (RNNs) trained with machine learning techniques on...

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CBMM spotlight

Pouya Bashivan: Neuro-Computational Vision

Pouya Bashivan: Neuro-Computational Vision

Associated Research Thrust(s):

Neural Circuits for Intelligence, Theoretical Frameworks for Intelligence

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Highlighted publications

CBMM Memo No:

116

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

CBMM Memo No:

115

A. Banburski, De La Torre, F., Pant, N., Shastri, I., and Poggio, T., “Distribution of Classification Margins: Are All Data Equal?”. 2021.

CBMM Memo No:

114

T. Poggio, “From Associative Memories to Powerful Machines”. 2021.

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Featured video

Embedded thumbnail for Banach Space Representer Theorems for Neural Networks

Banach Space Representer Theorems for Neural Networks

Prof. Robert D. Nowak, University of Wisconsin-Madison
Abstract: This talk presents a variational framework to understand the properties of functions learned by neural networks fit to data. The...

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