Unpacking the bias of large language models
In a new study, researchers discover the root cause of a type of bias in LLMs, paving the way for more accurate and reliable AI systems.
Melding data, systems, and society
A new book from Professor Munther Dahleh details the creation of a unique kind of transdisciplinary center, uniting many specialties through a common need for data science.
A new method for detecting gene-expression patterns linked to lineage progression, providing a powerful tool for studying cell state memory across biological systems.
MIT researchers developed a new approach for assessing predictions with a spatial dimension, like forecasting weather or mapping air pollution.
Toward video generative models of the molecular world
Starting with a single frame in a simulation, a new system uses generative AI to emulate the dynamics of molecules, connecting static molecular structures and developing blurry pictures into videos.
Beery, Farina, Ghassemi, Kim named AI2050 Early Career Fellows
The new crop of AI2050 Early Career Fellows was announced Dec. 10th.
The technique could make AI systems better at complex tasks that involve variability.
A causal theory for studying the cause-and-effect relationships of genes
By sidestepping the need for costly interventions, a new method could potentially reveal gene regulatory programs, paving the way for targeted treatments.
Empowering systemic racism research at MIT and beyond
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.
Researchers find large language models make inconsistent decisions about whether to call the police when analyzing surveillance videos.