Simpler models can outperform deep learning at climate prediction
New research shows the natural variability in climate data can cause AI models to struggle at predicting local temperature and rainfall.
Climate change
Eco-driving measures could significantly reduce vehicle emissions
New research shows automatically controlling vehicle speeds to mitigate traffic at intersections can cut carbon emissions between 11 and 22 percent.
The MIT-Portugal Program enters Phase 4
New phase will support continued exploration of ideas and solutions in fields ranging from AI to nanotech to climate — with emphasis on educational exchanges and entrepreneurship.
Taking the “training wheels” off clean energy
At the 2025 MIT Energy Conference, energy leaders from around the world discussed how to make green technologies competitive with fossil fuels.
MIT Maritime Consortium sets sail
A new international collaboration unites MIT and maritime industry leaders to develop nuclear propulsion technologies, alternative fuels, data-powered strategies for operation, and more.
Puzzling out climate change
Accenture Fellow Shreyaa Raghavan applies machine learning and optimization methods to explore ways to reduce transportation sector emissions.
The multifaceted challenge of powering AI
Providing electricity to power-hungry data centers is stressing grids, raising prices for consumers, and slowing the transition to clean energy.
Q&A: The climate impact of generative AI
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.
MIT delegation mainstreams biodiversity conservation at the UN Biodiversity Convention, COP16
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.
New AI tool generates realistic satellite images of future flooding
The method could help communities visualize and prepare for approaching storms.