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.
Emissions
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.
Confronting the AI/energy conundrum
The MIT Energy Initiative’s annual research symposium explores artificial intelligence as both a problem and a solution for the clean energy transition.
AI stirs up the recipe for concrete in MIT study
With demand for cement alternatives rising, an MIT team uses machine learning to hunt for new ingredients across the scientific literature.
New tool evaluates progress in reinforcement learning
“IntersectionZoo,” a benchmarking tool, uses a real-world traffic problem to test progress in deep reinforcement learning algorithms.
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.
A platform to expedite clean energy projects
Station A, founded by MIT alumni, makes the process of buying clean energy simple for property owners.
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.
Explained: Generative AI’s environmental impact
Rapid development and deployment of powerful generative AI models comes with environmental consequences, including increased electricity demand and water consumption.