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.
AI agents could soon become indistinguishable from humans online. Could “personhood credentials” protect people against digital imposters?
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.
A new algorithm helps robots practice skills like sweeping and placing objects, potentially helping them improve at important tasks in houses, hospitals, and factories.
In controlled experiments, MIT CSAIL researchers discover simulations of reality developing deep within LLMs, indicating an understanding of language beyond simple mimicry.
The model could help clinicians assess breast cancer stage and ultimately help in reducing overtreatment.
Neural network controllers provide complex robots with stability guarantees, paving the way for the safer deployment of autonomous vehicles and industrial machines.
The program focused on AI in health care, drawing on Takeda’s R&D experience in drug development and MIT’s deep expertise in AI.
MosaicML, co-founded by an MIT alumnus and a professor, made deep-learning models faster and more efficient. Its acquisition by Databricks broadened that mission.