Electrical engineering and computer science (EECS)
Electrical engineering and computer science (EECS)

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 present bold ideas for AI at MIT Generative AI Impact Consortium kickoff event

Presentations targeted high-impact intersections of AI and other areas, such as health care, business, and education.

A sounding board for strengthening the student experience

Composed of “computing bilinguals,” the Undergraduate Advisory Group provides vital input to help advance the mission of the MIT Schwarzman College of Computing.

Unpacking the bias of large language models

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.

Photonic processor could streamline 6G wireless signal processing

By performing deep learning at the speed of light, this chip could give edge devices new capabilities for real-time data analysis.

Melding data, systems, and society

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.

AI-enabled control system helps autonomous drones stay on target in uncertain environments

The system automatically learns to adapt to unknown disturbances such as gusting winds.

Envisioning a future where health care tech leaves some behind

The winning essay of the Envisioning the Future of Computing Prize puts health care disparities at the forefront.

Helping machines understand visual content with AI

Coactive, founded by two MIT alumni, has built an AI-powered platform to unlock new insights from content of all types.

Teaching AI models what they don’t know

A team of MIT researchers founded Themis AI to quantify AI model uncertainty and address knowledge gaps.