This intensive two-week course will give advanced students a “deep end” introduction to the problem of intelligence – how the brain produces intelligent behavior and how we may be able to replicate intelligence in machines. 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.

The course is limited to 25 students.

Room, and board at MBL will be supported by an NSF Science and Technology
Center award to the Center for Brains, Minds, and Machines.

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Course Faculty will include:
Edward Boyden
Robert Desimone
Winrich Freiwald
Nancy Kanwisher
Boris Katz
Gabriel Kreiman
Ken Nakayama
Lorenzo Rosasco
Laura Schulz
Joshua Tenenbaum
Shimon Ullman
Leslie Valiant
Patrick Winston