Training machines to learn more like humans do
Researchers identify a property that helps computer vision models learn to represent the visual world in a more stable, predictable way.
The answer may be blowing in the wind
The MIT Energy Initiative’s Spring Symposium highlights the vast potential of offshore turbines in decarbonizing the grid.
US and UAE governments highlight early warning system for climate resilience
One of MIT’s five Climate Grand Challenges flagship projects, the Jameel Observatory-CREWSnet project will pilot in Bangladesh and Sudan to help communities adapt to the impacts of climate change.
An unprecedented view of gene regulation
MIT engineers’ new technique analyzes the 3D organization of the genome at a resolution 100 times higher than before.
MIT HUMANS project breaks down borders, empowering global voices to reach for the stars
The HUMANS nanowafer, an MIT Space Exploration Initiative student-led project, will travel to the ISS this month, and later to the moon, carrying messages in more than 64 languages from over 80 countries.
After Amazon, an ambition to accelerate American manufacturing
Jeff Wilke SM '93, former CEO of Amazon’s Worldwide Consumer business, brings his LGO playbook to his new mission of revitalizing manufacturing in the U.S.
There’s something for everyone at the “front porch of campus”
The MIT Sailing Pavilion, the oldest collegiate organization of its kind, offers community members a chance to sail for free — or just enjoy the good vibes.
Researchers create a tool for accurately simulating complex systems
The system they developed eliminates a source of bias in simulations, leading to improved algorithms that can boost the performance of applications.
Third annual MIT Research Slam showcase highlights PhD and postdoc communication skills
The 2023 competition featured three-minute talks on cutting-edge research from across MIT in an engaging, live competition.
Researchers develop novel AI-based estimator for manufacturing medicine
A collaborative research team from the MIT-Takeda Program combined physics and machine learning to characterize rough particle surfaces in pharmaceutical pills and powders.