In a unique research collaboration, students make the case for less e-waste
SERC Scholars from around the MIT community examine the electronic hardware waste life cycle and climate justice.
SERC Scholars from around the MIT community examine the electronic hardware waste life cycle and climate justice.
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.
In a recent commentary, a team from MIT, Equality AI, and Boston University highlights the gaps in regulation for AI models and non-AI algorithms in health care.
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.
MIT CSAIL director and EECS professor named a co-recipient of the honor for her robotics research, which has expanded our understanding of what a robot can be.
Researchers develop “ContextCite,” an innovative method to track AI’s source attribution and detect potential misinformation.
First organized MIT delegation highlights the Institute's growing commitment to addressing climate change by showcasing research on biodiversity conservation, AI, and the role of local communities.
Researchers propose a simple fix to an existing technique that could help artists, designers, and engineers create better 3D models.
This new device uses light to perform the key operations of a deep neural network on a chip, opening the door to high-speed processors that can learn in real-time.
Marzyeh Ghassemi works to ensure health-care models are trained to be robust and fair.
The Tree-D Fusion system integrates generative AI and genus-conditioned algorithms to create precise simulation-ready models of 600,000 existing urban trees across North America.
MIT CSAIL researchers used AI-generated images to train a robot dog in parkour, without real-world data. Their LucidSim system demonstrates generative AI's potential for creating robotics training data.
Yiming Chen ’24, Wilhem Hector, Anushka Nair, and David Oluigbo will start postgraduate studies at Oxford next fall.
Members of MIT’s School of Engineering were honored in recognition of their scholarship, service, and overall excellence in the summer of 2024.