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 EECS faculty and CSAIL principal investigators Sara Beery, Marzyeh Ghassemi, and Yoon Kim (Credit: MIT EECS).
CSAIL article

Sara Beery, Marzyeh Ghassemi, and Yoon Kim, EECS faculty and CSAIL principal investigators, were awarded AI2050 Early Career Fellowships earlier this week for their pursuit of “bold and ambitious work on hard problems in AI.” They received this honor from Schmidt Futures, Eric and Wendy Schmidt’s philanthropic initiative that aims to accelerate scientific innovation.

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When users query a model, ContextCite highlights the specific sources from the external context that the AI relied upon for that answer. If the AI generates an inaccurate fact, for example, users can trace the error back to its source and understand the model’s reasoning (Credit: Alex Shipps/MIT CSAIL).
CSAIL article

Chatbots can wear a lot of proverbial hats: dictionary, therapist, poet, all-knowing friend. The artificial intelligence models that power these systems appear exceptionally skilled and efficient at providing answers, clarifying concepts, and distilling information. But to establish trustworthiness of content generated by such models, how can we really know if a particular statement is factual, a hallucination, or just a plain misunderstanding?

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alt="Regina Barzilay, MIT professor, CSAIL Principal Investigator, and Jameel Clinic AI Faculty Lead (Credit: WCVB)."
CSAIL article

Regina Barzilay, School of Engineering Distinguished Professor for AI and Health at MIT, CSAIL Principal Investigator, and Jameel Clinic AI Faculty Lead, has been awarded the 2025 Frances E. Allen Medal from the Institute of Electrical and Electronics Engineers (IEEE). Barzilay’s award recognizes the impact of her machine-learning algorithms on medicine and natural language processing.