MIT researchers develop an efficient way to train more reliable AI agents
The technique could make AI systems better at complex tasks that involve variability.
The technique could make AI systems better at complex tasks that involve variability.
By sidestepping the need for costly interventions, a new method could potentially reveal gene regulatory programs, paving the way for targeted treatments.
Researchers in the MIT Initiative on Combatting Systemic Racism are building an open data repository to advance research on racial inequity in domains like policing, housing, and health care.
Along with James Robinson, the professors are honored for work on the relationship between economic growth and political institutions.
Models show that an unexpected reduction in human-driven emissions led to a 10 percent decline in atmospheric mercury concentrations.
Researchers find large language models make inconsistent decisions about whether to call the police when analyzing surveillance videos.
Ortiz is an internationally recognized researcher in biotechnology and biomaterials, advanced and additive manufacturing, and sustainable and socially-directed materials design.
The approach can detect anomalies in data recorded over time, without the need for any training.
New center taps Institute-wide expertise to improve understanding of, and responses to, sustainability challenges.
The model could help clinicians assess breast cancer stage and ultimately help in reducing overtreatment.
A new technique enables users to compare several large models and choose the one that works best for their task.
PhD student Xinyi Zhang is developing computational tools for analyzing cells in the age of multimodal data.
Staff members receive recognition for their exceptional support of the MIT community.
Ammonia could be a nearly carbon-free maritime fuel, but without new emissions regulations, its impact on air quality could significantly impact human health.
Fifteen new faculty members join six of the school’s academic departments.