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Brains, Minds and Machines Summer Course 2021

Applications are now open for the 2021 edition of the Brain, Minds and Machines Summer Course in Woods Hole MA.

08/05/2021 – 08/26/2021

Link to application: https://www.mbl.edu/education/courses/brains-minds-and-machines/

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Virtual Brains, Minds and Machines Summer Course

Woods Hole, Massachussetts

Brains, Minds and Machines

Directors: Gabriel Kreiman, Boris Katz, Tomaso Poggio

August 10, 2020 through August 21, 2020
Please follow this link to the course web site

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How brain computations can inspire new paths in AI

Lecture presented at the BMM Summer School 2021 by Gabriel Kreiman

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Kreiman Lab News

Brains, Minds and Machines Summer Course 2020

Applications are now open for the 2020 edition of the Brains, Minds and Machines in Woods Hole, MA.

Directors: Gabriel Kreiman, Boston Children’s Hospital, Harvard Medical School; Boris Katz, Massachusetts Institute of Technology; and Tomaso Poggio, Massachusetts Institute of Technology
Location: Marine Biological Laboratory, in Woods Hole, MA.
Course Dates: August 6 – August 27, 2020
Application: https://www.mbl.edu/education/courses/brains-minds-and-machines/
Application deadline: April 27, 2020
Schedule:  TBA

Course Description

The basis of intelligence – how the brain produces intelligent behavior and how we may be able to replicate intelligence in machines – is arguably the greatest problem in science and technology. To solve it, we will need to understand how human intelligence emerges from computations in neural circuits, with rigor sufficient to reproduce similar intelligent behavior in machines. Success in this endeavor ultimately will enable us to understand ourselves better, to produce smarter machines, and perhaps even to make ourselves smarter. Today’s AI technologies, such as Watson and Siri, are impressive, but their domain specificity and reliance on vast numbers of labeled examples are obvious limitations; few view this as brain-like or human intelligence. The synergistic combination of cognitive science, neurobiology, engineering, mathematics, and computer science holds the promise to build much more robust and sophisticated algorithms implemented in intelligent machines. The goal of this course is to help produce a community of leaders that is equally knowledgeable in neuroscience, cognitive science, and computer science and will lead the development of true biologically inspired AI.

The class discussions will cover a range of topics, including:

  • Neuroscience: neurons and models
  • Computational vision
  • Biological vision
  • Machine learning
  • Bayesian inference
  • Planning and motor control
  • Memory
  • Social cognition
  • Inverse problems & well-posedness
  • Audition and speech processing
  • Natural language processing

These discussions will be complemented in the first week by MathCamps and NeuroCamps, to refresh the necessary background. Throughout the course, students will participate in workshops and tutorials to gain hands-on experience with these topics.

Core presentations will be given jointly by neuroscientists, cognitive scientists, and computer scientists. Lectures will be followed by afternoons of computational labs, with additional evening research seminars. To reinforce the theme of collaboration between (computer science + math) and (neuroscience + cognitive science), exercises and projects often will be performed in teams that combine students with both backgrounds.

The course will culminate with student presentations of their projects. These projects provide the opportunity for students to work closely with the resident faculty, to develop ideas that grow out of the lectures and seminars, and to connect these ideas with problems from the students’ own research at their home institutions.

This course aims to cross-educate computer engineers and neuroscientists; it is appropriate for graduate students, postdocs, and faculty in computer science or neuroscience. Students are expected to have a strong background in one discipline (such as neurobiology, physics, engineering, and mathematics). Our goal is to develop the science and the technology of intelligence and to help train a new generation of scientists that will leverage the progress in neuroscience, cognitive science, and computer science. The course is limited to 35 students.

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The Brains, Minds and Machines Course is now on OpenCouseWare

Brains, Minds and Machines Summer Course

Instructor(s)

BMM Summer Course

Prof. Tomaso Poggio
(Course Director, MIT)

Prof. Gabriel Kreiman
(Course Director, Harvard)

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, which studies the mind; neuroscience, which studies the brain; and computer science and artificial intelligence, which study the computations needed to develop intelligent machines. Materials are drawn from the Brains, Minds and Machines Summer Course offered annually at the Marine Biological Laboratory in Woods Hole, MA, taught by faculty affiliated with the Center for Brains, Minds and Machines headquartered at MIT. Elements of the summer course are integrated into the MIT course, 9.523 Aspects of a Computational Theory of Intelligence.