Improving health, one machine learning system at a time
Marzyeh Ghassemi works to ensure health-care models are trained to be robust and fair.
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.
Despite its impressive output, generative AI doesn’t have a coherent understanding of the world
Researchers show that even the best-performing large language models don’t form a true model of the world and its rules, and can thus fail unexpectedly on similar tasks.
Researchers find large language models make inconsistent decisions about whether to call the police when analyzing surveillance videos.
The approach can detect anomalies in data recorded over time, without the need for any training.
Elaine Liu: Charging ahead
The MIT senior calculates how renewables and EVs impact the grid.
Three from MIT awarded 2024 Guggenheim Fellowships
MIT professors Roger Levy, Tracy Slatyer, and Martin Wainwright appointed to the 2024 class of “trail-blazing fellows.”
Using generative AI to improve software testing
MIT spinout DataCebo helps companies bolster their datasets by creating synthetic data that mimic the real thing.
Dealing with the limitations of our noisy world
Tamara Broderick uses statistical approaches to understand and quantify the uncertainty that can affect study results.
Department of EECS Announces 2024 Promotions
The Department of Electrical Engineering and Computer Science (EECS) is proud to announce multiple promotions.