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.
Speakers
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Director, MIT Quest for IntelligenceCo-Director, Center for Brains, Minds, and MachinesPeter de Florez Professor, Department of Brain and Cognitive SciencesMcGovern Institute for Brain Research- Computational Neuroscience
- Machine Learning
- Computer Vision
MissionsProjects -
Scientific Advisor, MIT Quest for IntelligenceEugene McDermott Professor, Department of Brain and Cognitive SciencesComputer Science and Artificial Intelligence LaboratoryCo-Director, Center for Brains, Minds, and Machines- Machine Learning
- Computational Cognition
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Director of Science, MIT Quest for IntelligenceProfessor, Department of Brain and Cognitive SciencesComputer Science and Artificial Intelligence Laboratory- Computational Cognition
- Machine Learning
- AI Explainability
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Walter A. Rosenblith Professor, Department of Brain and Cognitive SciencesMcGovern Institute for Brain Research- Computational Cognition
- Computational Neuroscience
Missions -
Director of Research, MIT Quest for IntelligencePanasonic Professor, Department of Electrical Engineering and Computer ScienceComputer Science and Artificial Intelligence Laboratory- AI Robotics
- Machine Learning
- Computer Vision
Missions -
Professor, Department of Brain and Cognitive SciencesInvestigator, McGovern Institute for Brain ResearchInvestigator. Howard Hughes Medical InstituteMissions -
Professor, Department of Brain and Cognitive SciencesAssociate Investigator, McGovern Institute- Computational Neuroscience
- Computational Cognition
Missions -
Associate Professor of Neuroscience, Department of Brain and Cognitive SciencesInvestigator, McGovern Institute for Brain Research- Natural Language Processing
Missions -
Associate Professor, Department of Electrical Engineering and Computer ScienceComputer Science and Artificial Intelligence Laboratory- Natural Language Processing
- Machine Learning
Missions -
Breene M. Kerr (1951) Professor, Department of Nuclear Science and EngineeringProfessor, Department of Materials Science and Engineering- Nanotechnology
Missions -
Patrick J. McGovern Professor, MIT Sloan School of ManagementFounding Director, MIT Center for Collective IntelligenceMissions -
John and Dorothy Wilson Professor, Department of Brain & Cognitive SciencesAssociate Department Head, Department of Brain and Cognitive SciencesInvestigator, Center for Brains, Minds and MachinesMacVicar Faculty Fellow -
John W. Jarve (1978) Professor, Brain and Cognitive SciencesAssociate Dean, School of ScienceMissions -
Director of Modeling and InferencePrincipal Research Scientist, Department of Brain and Cognitive Sciences -
- Computational Neuroscience
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Schedule
Morning program
Afternoon program
Closing remarks
