Puzzling out climate change
Accenture Fellow Shreyaa Raghavan applies machine learning and optimization methods to explore ways to reduce transportation sector emissions.
Accenture Fellow Shreyaa Raghavan applies machine learning and optimization methods to explore ways to reduce transportation sector emissions.
Providing electricity to power-hungry data centers is stressing grids, raising prices for consumers, and slowing the transition to clean energy.
As the use of generative AI continues to grow, Lincoln Laboratory’s Vijay Gadepally describes what researchers and consumers can do to help mitigate its environmental impact.
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.
The method could help communities visualize and prepare for approaching storms.
In a talk at MIT, White House science advisor Arati Prabhakar outlined challenges in medicine, climate, and AI, while expressing resolve to tackle hard problems.
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.
Progress on the energy transition depends on collective action benefiting all stakeholders, agreed participants in MITEI’s annual research conference.
Developed by MIT RAISE, the Day of AI curriculum empowers K-12 students to collaborate on local and global challenges using AI.
A new downscaling method leverages machine learning to speed up climate model simulations at finer resolutions, making them usable on local levels.