MIT Maritime Consortium sets sail
A new international collaboration unites MIT and maritime industry leaders to develop nuclear propulsion technologies, alternative fuels, data-powered strategies for operation, and more.
AI tool generates high-quality images faster than state-of-the-art approaches
Researchers fuse the best of two popular methods to create an image generator that uses less energy and can run locally on a laptop or smartphone.
At the core of problem-solving
Stuart Levine ’97, director of MIT’s BioMicro Center, keeps departmental researchers at the forefront of systems biology.
“An AI future that honors dignity for everyone”
As artificial intelligence develops, we must ask vital questions about ourselves and our society, Ben Vinson III contends in the 2025 Compton Lecture.
Making airfield assessments automatic, remote, and safe
U.S. Air Force engineer and PhD student Randall Pietersen is using AI and next-generation imaging technology to detect pavement damage and unexploded munitions.
Robotic helper making mistakes? Just nudge it in the right direction
New research could allow a person to correct a robot’s actions in real-time, using the kind of feedback they’d give another human.
3 Questions: Visualizing research in the age of AI
Felice Frankel discusses the implications of generative AI when communicating science visually.
Markus Buehler receives 2025 Washington Award
Materials scientist is honored for his academic leadership and innovative research that bridge engineering and nature.
Collaborating to advance research and innovation on essential chips for AI
Agreement between MIT Microsystems Technology Laboratories and GlobalFoundries aims to deliver power efficiencies for data centers and ultra-low power consumption for intelligent devices at the edge.
An ancient RNA-guided system could simplify delivery of gene editing therapies
The programmable proteins are compact, modular, and can be directed to modify DNA in human cells.
AI system predicts protein fragments that can bind to or inhibit a target
FragFold, developed by MIT Biology researchers, is a computational method with potential for impact on biological research and therapeutic applications.
Like human brains, large language models reason about diverse data in a general way
A new study shows LLMs represent different data types based on their underlying meaning and reason about data in their dominant language.
MIT spinout maps the body’s metabolites to uncover the hidden drivers of disease
ReviveMed uses AI to gather large-scale data on metabolites — molecules like lipids, cholesterol, and sugar — to match patients with therapeutics.
AI model deciphers the code in proteins that tells them where to go
Whitehead Institute and CSAIL researchers created a machine-learning model to predict and generate protein localization, with implications for understanding and remedying disease.
Gift from Sebastian Man ’79, SM ’80 supports MIT Stephen A. Schwarzman College of Computing building
Alumnus is the first major donor to support the building since Stephen A. Schwarzman’s foundational gift.