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

In an analysis of over 160,000 transplant candidates, researchers found that race is linked to how likely an organ offer is to be accepted on behalf of a patient.

By leveraging reflections from wireless signals like Wi-Fi, the system could allow robots to find and manipulate items that are blocked from view.

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.

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.

The low-cost, scalable technology can seamlessly integrate high-speed gallium nitride transistors onto a standard silicon chip.

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.

Researchers designed a tiny receiver chip that is more resilient to interference, which could enable smaller 5G “internet of things” devices with longer battery lives.

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