The “PRoC3S” method helps an LLM create a viable action plan by testing each step in a simulation. This strategy could eventually aid in-home robots to complete more ambiguous chore requests.

A better understanding of construction industry stakeholders’ motivations can lead to greater adoption of circular practices.

Using high-powered lasers, this new method could help biologists study the body’s immune responses and develop new medicines.

A new technique identifies and removes the training examples that contribute most to a machine-learning model’s failures.

Using LLMs to convert machine-learning explanations into readable narratives could help users make better decisions about when to trust a model.

The MIT Health and Life Sciences Collaborative will bring together researchers from across the Institute to deliver health care solutions at scale.

Researchers develop “ContextCite,” an innovative method to track AI’s source attribution and detect potential misinformation.

MIT engineers show how detailed mapping of weather conditions and energy demand can guide optimization for siting renewable energy installations.

MIT chemical engineers designed an environmentally friendly alternative to the microbeads used in some health and beauty products.

MIT engineers developed the largest open-source dataset of car designs, including their aerodynamics, that could speed design of eco-friendly cars and electric vehicles.