The sweet taste of a new idea
Sendhil Mullainathan brings a lifetime of unique perspectives to research in behavioral economics and machine learning.
Data
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.
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.
Validation technique could help scientists make more accurate forecasts
MIT researchers developed a new approach for assessing predictions with a spatial dimension, like forecasting weather or mapping air pollution.