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.
Research
3 Questions: Enhancing last-mile logistics with machine learning
MIT Center for Transportation and Logistics Director Matthias Winkenbach uses AI to make vehicle routing more efficient and adaptable for unexpected events.
New AI method captures uncertainty in medical images
By providing plausible label maps for one medical image, the Tyche machine-learning model could help clinicians and researchers capture crucial information.
A faster, better way to prevent an AI chatbot from giving toxic responses
Researchers create a curious machine-learning model that finds a wider variety of prompts for training a chatbot to avoid hateful or harmful output.
When an antibiotic fails: MIT scientists are using AI to target “sleeper” bacteria
Most antibiotics target metabolically active bacteria, but with artificial intelligence, researchers can efficiently screen compounds that are lethal to dormant microbes.
A new computational technique could make it easier to engineer useful proteins
MIT researchers plan to search for proteins that could be used to measure electrical activity in the brain.
Most work is new work, long-term study of U.S. census data shows
The majority of U.S. jobs are in occupations that have emerged since 1940, MIT research finds — telling us much about the ways jobs are created and lost.
Does technology help or hurt employment?
Combing through 35,000 job categories in U.S. census data, economists found a new way to quantify technology’s effects on job loss and creation.
MIT launches Working Group on Generative AI and the Work of the Future
New initiative is convening leading companies and nonprofits with support from Google’s Community Grants Fund.
Second round of seed grants awarded to MIT scholars studying the impact and applications of generative AI
The 16 finalists — representing every school at MIT — will explore generative AI’s impact on privacy, art, drug discovery, aging, and more.