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Advances in the quest to understand intelligence

Friday, November 4, 2022
Singleton Auditorium, Building 46
MIT dome with autumnal trees

Our vision, our most recent progress, and the future of research on the Science and Engineering of Intelligence

MIT's Quest for Intelligence aims to understand intelligence by tightly coupling scientific enquiry and rigorous engineering to address real-world problems that are beyond current machine capabilities but within the ability of natural intelligence. To achieve this vision, the study of natural intelligence and efforts to build intelligent systems must be treated as two interlocked aspects of the same grand challenge, with neuroscientists and cognitive scientists working alongside computer scientists and software engineers.

On November 4, 2022, researchers from the Quest and its science driver — the Center for Brains, Minds, and Machines —  shared the latest progress on understanding natural intelligence and how we aim to use that scientific progress to drive the future of AI and other impact areas. We were happy to welcome supporters, industry collaborators, and members of the MIT community to a day-long series of presentations and conversations about our vision, our most recent progress, and the future of research on the Science and Engineering of Intelligence. 

Most of the presentations were recorded and are available on our YouTube channel or linked from the listings below. 


  • Portrait of Tomaso Poggio, MIT
    Eugene McDermott Professor, Department of Brain and Cognitive Sciences
    Co-Director, Center for Brains, Minds and Machines
    Scientific Advisor, MIT Quest for Intelligence
    • Machine Learning
    • Computational Cognition
  • Nancy Kanwisher
    Walter A. Rosenblith Professor, Department of Brain and Cognitive Sciences
    McGovern Institute for Brain Research
    • Computational Cognition
    • Computational Neuroscience
  • Ila Fiete
    Professor, Department of Brain and Cognitive Sciences
    Associate Investigator, McGovern Institute
    • Computational Neuroscience
    • Computational Cognition
  • Photo of Evelina Fedorenko
    Associate Professor of Neuroscience, Department of Brain and Cognitive Sciences
    Investigator, McGovern Institute for Brain Research
    • Natural Language Processing
  • photo of Jacob Andreas
    Associate Professor, Department of Electrical Engineering and Computer Science
    Computer Science and Artificial Intelligence Laboratory
    • Natural Language Processing
    • Machine Learning
  • Ed Boyden

    Edward Boyden

    Y. Eva Tan Professor in Neurotechnology
    Co-Director, K. Lisa Yang Center for Bionics
  • photo of Matt Wilson

    Matt Wilson

    Assoc. Dept. Head and Sherman Fairchild Prof. of Neuroscience, Dept. of Brain & Cognitive Sciences,
    The Picower Institute for Learning and Memory


Morning program

9:00 AM - 9:10 AM
9:10 AM - 9:30 AM
9:30 AM - 9:45 AM
9:45 AM - 10:00 AM
10:00 AM - 12:15 PM
10:40 AM - 11:00 AM
11:25 AM - 11:55 AM
11:55 AM - 12:20 PM

Afternoon program

1:15 PM - 2:15 PM
1:25 PM - 1:35 PM
1:35 PM - 1:45 PM

Brain-inspired artificial neurons Bilge Yildiz

1:45 PM - 1:55 PM
1:55 PM - 2:05 PM
2:05 PM - 2:15 PM
2:45 PM - 4:00 PM
3:25 PM - 3:50 PM
3:50 PM - 4:00 PM

Closing remarks

Event Organizers

Event Questions? Contact Allison Provaire (