LLMs factor in unrelated information when recommending medical treatments
Researchers find nonclinical information in patient messages — like typos, extra white space, and colorful language — reduces the accuracy of an AI model.
Researchers find nonclinical information in patient messages — like typos, extra white space, and colorful language — reduces the accuracy of an AI model.
Presentations targeted high-impact intersections of AI and other areas, such as health care, business, and education.
Composed of “computing bilinguals,” the Undergraduate Advisory Group provides vital input to help advance the mission of the MIT Schwarzman College of Computing.
In a new study, researchers discover the root cause of a type of bias in LLMs, paving the way for more accurate and reliable AI systems.
By performing deep learning at the speed of light, this chip could give edge devices new capabilities for real-time data analysis.
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.
A new book from Professor Munther Dahleh details the creation of a unique kind of transdisciplinary center, uniting many specialties through a common need for data science.
Forget optimists vs. Luddites. Most people evaluate AI based on its perceived capability and their need for personalization.
The system automatically learns to adapt to unknown disturbances such as gusting winds.
The winning essay of the Envisioning the Future of Computing Prize puts health care disparities at the forefront.