AI learns how vision and sound are connected, without human intervention
This new machine-learning model can match corresponding audio and visual data, which could someday help robots interact in the real world.
Data
Learning how to predict rare kinds of failures
Researchers are developing algorithms to predict failures when automation meets the real world in areas like air traffic scheduling or autonomous vehicles.
The sweet taste of a new idea
Sendhil Mullainathan brings a lifetime of unique perspectives to research in behavioral economics and machine learning.
Q&A: A roadmap for revolutionizing health care through data-driven innovation
A new book coauthored by MIT’s Dimitris Bertsimas explores how analytics is driving decisions and outcomes in health care.
New tool evaluates progress in reinforcement learning
“IntersectionZoo,” a benchmarking tool, uses a real-world traffic problem to test progress in deep reinforcement learning algorithms.
Novel AI model inspired by neural dynamics from the brain
New type of “state-space model” leverages principles of harmonic oscillators.
New method efficiently safeguards sensitive AI training data
The approach maintains an AI model’s accuracy while ensuring attackers can’t extract secret information.
Could LLMs help design our next medicines and materials?
A new method lets users ask, in plain language, for a new molecule with certain properties, and receive a detailed description of how to synthesize it.
Vana is letting users own a piece of the AI models trained on their data
More than 1 million people are contributing their data to Vana’s decentralized network, which started as an MIT class project.
At the core of problem-solving
Stuart Levine ’97, director of MIT’s BioMicro Center, keeps departmental researchers at the forefront of systems biology.