School of Engineering

Auto Added by WPeMatico

Why it’s critical to move beyond overly aggregated machine-learning metrics

ai, AI (Artificial Intelligence), Artificial Intelligence, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Electrical engineering and computer science (EECS), Health care, Institute for Medical Engineering and Science (IMES), Laboratory for Information and Decision Systems (LIDS), Machine Learning, MIT Schwarzman College of Computing, Research, School of Engineering, Technology and society

MIT researchers have identified significant examples of machine-learning model failure when those models are applied to data other than what they were trained on, raising questions about the need to test whenever a model is deployed in a new setting.“We demonstrate that even when you train models on large amounts of data, and choose the […]

Why it’s critical to move beyond overly aggregated machine-learning metrics Read More »

Generative AI tool helps 3D print personal items that sustain daily use

3-D printing, ai, AI (Artificial Intelligence), Artificial Intelligence, Center for Bits and Atoms, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Design, Electrical engineering and computer science (EECS), Fabrication, Invention, Machine Learning, MIT Schwarzman College of Computing, School of Engineering

Generative artificial intelligence models have left such an indelible impact on digital content creation that it’s getting harder to recall what the internet was like before it. You can call on these AI tools for clever projects such as videos and photos — but their flair for the creative hasn’t quite crossed over into the

Generative AI tool helps 3D print personal items that sustain daily use Read More »

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

At MIT, a continued commitment to understanding intelligence Read More »

3 Questions: How AI could optimize the power grid

ai, AI (Artificial Intelligence), Algorithms, Alternative energy, Artificial Intelligence, Batteries, Climate change, Computer science and technology, Electrical engineering and computer science (EECS), Energy, Energy storage, Faculty, Interview, Laboratory for Information and Decision Systems (LIDS), Machine Learning, MIT Schwarzman College of Computing, Pollution, Research, School of Engineering, Sustainability, Sustainable computing

Artificial intelligence has captured headlines recently for its rapidly growing energy demands, and particularly the surging electricity usage of data centers that enable the training and deployment of the latest generative AI models. But it’s not all bad news — some AI tools have the potential to reduce some forms of energy consumption and enable cleaner grids.One

3 Questions: How AI could optimize the power grid Read More »

Decoding the Arctic to predict winter weather

ai, AI (Artificial Intelligence), Artificial Intelligence, Civil and environmental engineering, Climate, Computer science and technology, Earth and atmospheric sciences, Machine Learning, Natural disasters, Profile, Research, School of Engineering, Staff, Technology and society, Weather

Every autumn, as the Northern Hemisphere moves toward winter, Judah Cohen starts to piece together a complex atmospheric puzzle. Cohen, a research scientist in MIT’s Department of Civil and Environmental Engineering (CEE), has spent decades studying how conditions in the Arctic set the course for winter weather throughout Europe, Asia, and North America. His research

Decoding the Arctic to predict winter weather Read More »

MIT scientists investigate memorization risk in the age of clinical AI

ai, AI (Artificial Intelligence), Artificial Intelligence, Broad Institute, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, cybersecurity, Electrical engineering and computer science (EECS), ethics, Health care, Health sciences and technology, Human-computer interaction, Institute for Medical Engineering and Science (IMES), Jameel Clinic, Laboratory for Information and Decision Systems (LIDS), Machine Learning, MIT Schwarzman College of Computing, National Science Foundation (NSF), Privacy, Public health, Research, School of Engineering, Technology and society

What is patient privacy for? The Hippocratic Oath, thought to be one of the earliest and most widely known medical ethics texts in the world, reads: “Whatever I see or hear in the lives of my patients, whether in connection with my professional practice or not, which ought not to be spoken of outside, I

MIT scientists investigate memorization risk in the age of clinical AI Read More »

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

MIT in the media: 2025 in review Read More »

Guided learning lets “untrainable” neural networks realize their potential

Algorithms, Artificial Intelligence, Center for Brains Minds and Machines, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, data, Defense Advanced Research Projects Agency (DARPA), Electrical engineering and computer science (EECS), Machine Learning, MIT Schwarzman College of Computing, MIT-IBM Watson AI Lab, National Science Foundation (NSF), Networks, Neuroscience, Research, School of Engineering

Even networks long considered “untrainable” can learn effectively with a bit of a helping hand. Researchers at MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) have shown that a brief period of alignment between neural networks, a method they call guidance, can dramatically improve the performance of architectures previously thought unsuitable for modern tasks.Their findings

Guided learning lets “untrainable” neural networks realize their potential Read More »

A new way to increase the capabilities of large language models

Algorithms, Artificial Intelligence, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, data, Electrical engineering and computer science (EECS), Machine Learning, MIT Schwarzman College of Computing, MIT-IBM Watson AI Lab, Research, School of Engineering

Most languages use word position and sentence structure to extract meaning. For example, “The cat sat on the box,” is not the same as “The box was on the cat.” Over a long text, like a financial document or a novel, the syntax of these words likely evolves. Similarly, a person might be tracking variables in

A new way to increase the capabilities of large language models Read More »

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

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