Brain and cognitive sciences

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Alexander Rakhlin named director of the MIT Statistics and Data Science Center

ai, AI (Artificial Intelligence), Alumni/ae, Artificial Intelligence, Brain and cognitive sciences, Computer science and technology, Electrical engineering and computer science (EECS), Faculty, IDSS, Leadership, Machine Learning, MIT Schwarzman College of Computing, School of Engineering, School of Science, Statistics

Alexander “Sasha” Rakhlin PhD ’06, the Distinguished Professor in Data, Systems, and Society at the MIT Institute for Data, Systems, and Society (IDSS); and a professor of brain and cognitive sciences at MIT, has been named the next director of the MIT Statistics and Data Science Center (SDSC). Rakhlin succeeds Ankur Moitra, the Norbert Wiener Professor of Mathematics, […]

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MIT in the media: Exploring how curiosity-driven science is an essential ingredient in America’s success

ai, AI (Artificial Intelligence), Artificial Intelligence, Bioengineering and biotechnology, Brain and cognitive sciences, Broad Institute, Comparative Media Studies/Writing, Computer Science and Artificial Intelligence Laboratory (CSAIL), Curiosity, Funding, Health sciences and technology, Innovation and Entrepreneurship (I&E), Mathematics, MIT Schwarzman College of Computing, MIT Sloan School of Management, Physics, Picower Institute, President Sally Kornbluth, Quantum Computing, Research, School of Architecture and Planning, School of Engineering, School of Humanities Arts and Social Sciences, School of Science, space exploration

Over the past 80 years, America’s bold, sustained investment in scientific research, and the discoveries, ideas and innovations that flowed from it made America a world leader. The nation’s scientific leadership has been essential to our shared prosperity and national security, and delivered real benefits for all Americans.On June 16, Scientific American released a special section,

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Improving understanding with language

ai, AI (Artificial Intelligence), Artificial Intelligence, Behavior, Brain and cognitive sciences, Communications, Law, Linguistics, MISTI, Policy, Politics, Profile, School of Humanities Arts and Social Sciences, School of Science, Students, Undergraduate

When she was a child, MIT senior Olivia Honeycutt would spend summers on her grandparents’ farm in rural Alabama outside Birmingham. The practical and cultural differences between farm and city life became more pronounced by comparison. “Life and the way we lived it slowed down on the farm,” she says. “It was a nice change

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Beacon Biosignals is mapping the brain during sleep

ai, AI (Artificial Intelligence), Alumni/ae, Alzheimer's, Artificial Intelligence, Brain and cognitive sciences, Disease, Harvard-MIT Health Sciences and Technology, Health care, Health sciences and technology, Innovation and Entrepreneurship (I&E), Institute for Medical Engineering and Science (IMES), Machine Learning, Mental health, Neuroscience, Parkinson's, School of Engineering, School of Science, Startups

The human brain remains one of the most fascinating and perplexing mysteries in medicine. Scientists still struggle to match neurological activity with brain function and detect problems early, slowing efforts to treat neurological disorders and other diseases.Beacon Biosignals is working to make sense of the brain by monitoring its activity while people sleep. The company,

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AI algorithm enables tracking of vital white matter pathways

ai, AI (Artificial Intelligence), Algorithms, Alzheimer's, Artificial Intelligence, Brain and cognitive sciences, Department of Defense (DoD), Health care, Health sciences and technology, Imaging, Institute for Medical Engineering and Science (IMES), National Institutes of Health (NIH), Neuroscience, Parkinson's, Picower Institute, Research, School of Engineering, School of Science

The signals that drive many of the brain and body’s most essential functions — consciousness, sleep, breathing, heart rate, and motion — course through bundles of “white matter” fibers in the brainstem, but imaging systems so far have been unable to finely resolve these crucial neural cables. That has left researchers and doctors with little

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At MIT, a continued commitment to understanding intelligence

ai, AI (Artificial Intelligence), Artificial Intelligence, Brain and cognitive sciences, Center for Brains Minds and Machines, Electrical engineering and computer science (EECS), Giving, MIT Schwarzman College of Computing, MIT Siegel Family Quest for Intelligence, Neuroscience, Research, School of Engineering, School of Science

The MIT Siegel Family Quest for Intelligence (SQI), a research unit in the MIT Schwarzman College of Computing, brings together researchers from across MIT who combine their diverse expertise to understand intelligence through tightly coupled scientific inquiry and rigorous engineering. These researchers engage in collaborative efforts spanning science, engineering, the humanities, and more. SQI seeks to

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A “scientific sandbox” lets researchers explore the evolution of vision systems

Artificial Intelligence, Brain and cognitive sciences, Center for Brains Minds and Machines, Computer science and technology, Computer vision, Defense Advanced Research Projects Agency (DARPA), Imaging, Machine Learning, Media Lab, Research, School of Architecture and Planning, School of Science, Sensors

Why did humans evolve the eyes we have today?While scientists can’t go back in time to study the environmental pressures that shaped the evolution of the diverse vision systems that exist in nature, a new computational framework developed by MIT researchers allows them to explore this evolution in artificial intelligence agents.The framework they developed, in

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Enabling small language models to solve complex reasoning tasks

Algorithms, Artificial Intelligence, Brain and cognitive sciences, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Defense Advanced Research Projects Agency (DARPA), Electrical engineering and computer science (EECS), Machine Learning, MIT Schwarzman College of Computing, MIT Siegel Family Quest for Intelligence, MIT-IBM Watson AI Lab, National Science Foundation (NSF), Research, School of Engineering, School of Science

As language models (LMs) improve at tasks like image generation, trivia questions, and simple math, you might think that human-like reasoning is around the corner. In reality, they still trail us by a wide margin on complex tasks. Try playing Sudoku with one, for instance, where you fill in numbers one through nine in such

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Understanding the nuances of human-like intelligence

Artificial Intelligence, Brain and cognitive sciences, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Electrical engineering and computer science (EECS), Faculty, Machine Learning, MIT Schwarzman College of Computing, Profile, School of Engineering

What can we learn about human intelligence by studying how machines “think?” Can we better understand ourselves if we better understand the artificial intelligence systems that are becoming a more significant part of our everyday lives?These questions may be deeply philosophical, but for Phillip Isola, finding the answers is as much about computation as it

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The cost of thinking

Artificial Intelligence, Brain and cognitive sciences, Computer science and technology, Machine Learning, McGovern Institute, Neuroscience, Research, School of Science

Large language models (LLMs) like ChatGPT can write an essay or plan a menu almost instantly. But until recently, it was also easy to stump them. The models, which rely on language patterns to respond to users’ queries, often failed at math problems and were not good at complex reasoning. Suddenly, however, they’ve gotten a

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