The technique could make AI systems better at complex tasks that involve variability.
Advancing urban tree monitoring with AI-powered digital twins
The Tree-D Fusion system integrates generative AI and genus-conditioned algorithms to create precise simulation-ready models of 600,000 existing urban trees across North America.
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.
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.
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.
Researchers argue that in health care settings, “responsible use” labels could ensure AI systems are deployed appropriately.
3 Questions: How to prove humanity online
AI agents could soon become indistinguishable from humans online. Could “personhood credentials” protect people against digital imposters?
Four Recipients Announced for new Transformative Research Funds
The department is pleased to announce the four inaugural recipients of the Transformative Research Fund, an exciting new funding opportunity designed to facilitate bold and pivotal research, especially that which applies recent breakthrough technologies (such as generative AI) to important problems with broad societal impact.