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3 Questions: Building predictive models to characterize tumor progression

ai, AI (Artificial Intelligence), Artificial Intelligence, Biology, Cancer, Computational biology, DNA, Evolution, Faculty, Genetics, Health sciences and technology, Institute for Medical Engineering and Science (IMES), Interview, Koch Institute, Machine Learning, Medicine, School of Science

Just as Darwin’s finches evolved in response to natural selection in order to endure, the cells that make up a cancerous tumor similarly counter selective pressures in order to survive, evolve, and spread. Tumors are, in fact, complex sets of cells with their own unique structure and ability to change. Today, artificial Intelligence and machine learning […]

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How Joseph Paradiso’s sensing innovations bridge the arts, medicine, and ecology

ai, AI (Artificial Intelligence), Alumni/ae, Artificial Intelligence, Digital technology, Ecology, Electronics, Environment, Faculty, Health, Internet of things, Machine Learning, Media Lab, Medicine, Physics, Profile, School of Architecture and Planning, School of Science, Sensors, Space, Wearable sensors, Wireless

Joseph Paradiso thinks that the most engaging research questions usually span disciplines. Paradiso was trained as a physicist and completed his PhD in experimental high-energy physics at MIT in 1981. His father was a photographer and filmmaker working at MIT, MIT Lincoln Laboratory, and the MITRE Corporation, so he grew up in a house where artists, scientists,

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Exposing biases, moods, personalities, and abstract concepts hidden in large language models

ai, AI (Artificial Intelligence), Algorithms, Artificial Intelligence, Computer science and technology, data, Machine Learning, Mathematics, Research, School of Science, Software

By now, ChatGPT, Claude, and other large language models have accumulated so much human knowledge that they’re far from simple answer-generators; they can also express abstract concepts, such as certain tones, personalities, biases, and moods. However, it’s not obvious exactly how these models represent abstract concepts to begin with from the knowledge they contain.Now a

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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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Katie Spivakovsky wins 2026 Churchill Scholarship

ai, AI (Artificial Intelligence), Artificial Intelligence, Awards, honors and fellowships, Biological engineering, Biology, Mathematics, MIT Schwarzman College of Computing, School of Engineering, School of Science, Students, Undergraduate

MIT senior Katie Spivakovsky has been selected as a 2026-27 Churchill Scholar and will undertake an MPhil in biological sciences at the Wellcome Sanger Institute at Cambridge University in the U.K. this fall.Spivakovsky, who is double-majoring in biological engineering and artificial intelligence, with minors in mathematics and biology, aims to integrate computation and bioengineering in

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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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MIT in the media: 2025 in review

Administration, Alumni/ae, Artificial Intelligence, Cambridge, Boston and region, Climate change, Community, Computer science and technology, Education, teaching, academics, Equity and inclusion, Faculty, Global, government, Health sciences and technology, Innovation and Entrepreneurship (I&E), MIT Schwarzman College of Computing, MIT Sloan School of Management, Policy, President Sally Kornbluth, Research, School of Architecture and Planning, School of Engineering, School of Humanities Arts and Social Sciences, School of Science, Social justice, Space, Staff, Students

“At MIT, innovation ranges from awe-inspiring technology to down-to-Earth creativity,” noted Chronicle, during a campus visit this year for an episode of the program. In 2025, MIT researchers made headlines across print publications, podcasts, and video platforms for key scientific advances, from breakthroughs in quantum and artificial intelligence to new efforts aimed at improving pediatric health

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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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3 Questions: Using computation to study the world’s best single-celled chemists

Artificial Intelligence, Bacteria, Biology, Electrical engineering and computer science (EECS), Evolution, Faculty, Genetics, Interview, Machine Learning, Microbes, MIT Schwarzman College of Computing, School of Engineering, School of Science

Today, out of an estimated 1 trillion species on Earth, 99.999 percent are considered microbial — bacteria, archaea, viruses, and single-celled eukaryotes. For much of our planet’s history, microbes ruled the Earth, able to live and thrive in the most extreme of environments. Researchers have only just begun in the last few decades to contend

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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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