Researchers find nonclinical information in patient messages — like typos, extra white space, and colorful language — reduces the accuracy of an AI model.
A new framework from the MIT-IBM Watson AI Lab supercharges language models, so they can reason over, interactively develop, and verify valid, complex travel agendas.
Lauren Hinkel | MIT-IBM Watson AI Lab •
mit
June 10, 2025
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~9 min
By eliminating redundant computations, a new data-driven method can streamline processes like scheduling trains, routing delivery drivers, or assigning airline crews.
Adam Zewe | MIT News •
mit
April 16, 2025
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~8 min