MIT Schwarzman College of Computing
MIT Schwarzman College of Computing

Study could lead to LLMs that are better at complex reasoning

Researchers developed a way to make large language models more adaptable to challenging tasks like strategic planning or process optimization.

Using generative AI to help robots jump higher and land safely

MIT CSAIL researchers combined GenAI and a physics simulation engine to refine robot designs. The result: a machine that out-jumped a robot designed by humans.

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.

Bringing meaning into technology deployment

The MIT Ethics of Computing Research Symposium showcases projects at the intersection of technology, ethics, and social responsibility.

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.

Inroads to personalized AI trip planning

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.

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.