Scientists use generative AI to answer complex questions in physics
A new technique that can automatically classify phases of physical systems could help scientists investigate novel materials.
Computer modeling
To build a better AI helper, start by modeling the irrational behavior of humans
A new technique can be used to predict the actions of human or AI agents who behave suboptimally while working toward unknown goals.
Using deep learning to image the Earth’s planetary boundary layer
Lincoln Laboratory researchers are using AI to get a better picture of the atmospheric layer closest to Earth's surface. Their techniques could improve weather and drought prediction.
MIT-derived algorithm helps forecast the frequency of extreme weather
The new approach “nudges” existing climate simulations closer to future reality.
Generative AI for smart grid modeling
MIT LIDS awarded funding from the Appalachian Regional Commission as part of a multi-state collaborative project to model and test new smart grid technologies for use in rural areas.
To excel at engineering design, generative AI must learn to innovate, study finds
AI models that prioritize similarity falter when asked to design something completely new.
How to help high schoolers prepare for the rise of artificial intelligence
A one-week summer program aims to foster a deeper understanding of machine-learning approaches in health among curious young minds.
MIT researchers combine deep learning and physics to fix motion-corrupted MRI scans
The challenge involves more than just a blurry JPEG. Fixing motion artifacts in medical imaging requires a more sophisticated approach.
Armando Solar-Lezama named inaugural Distinguished College of Computing Professor
The MIT Stephen A. Schwarzman College of Computing named Armando Solar-Lezama as the inaugural Distinguished College of Computing Professor, effective July 1. Solar-Lezama is the first person appointed to this…
Learning the language of molecules to predict their properties
Discovering new materials and drugs typically involves a manual, trial-and-error process that can take decades and cost millions of dollars. To streamline this process, scientists often use machine learning to…