By minimizing the need to drive around looking for a parking spot, this technique can save drivers up to 35 minutes — and give them a realistic estimate of total travel time.
Giti Tire used a four-step framework to cut emissions while growing profit.
Read MoreMacro, a modeling tool developed by the MIT Energy Initiative, enables energy-system planners to explore options for developing infrastructure to support decarbonized, reliable, and low-cost power grids.
Read MoreMIT faculty and MITEI member company experts address power demand from data centers.
Read MoreExplosive growth of AI data centers is expected to increase greenhouse gas emissions. Researchers are now seeking solutions to reduce these environmental harms.
Read MoreNew research shows the natural variability in climate data can cause AI models to struggle at predicting local temperature and rainfall.
Read MoreNew research shows automatically controlling vehicle speeds to mitigate traffic at intersections can cut carbon emissions between 11 and 22 percent.
Read MoreThe MIT Energy Initiative’s annual research symposium explores artificial intelligence as both a problem and a solution for the clean energy transition.
Read MoreWith demand for cement alternatives rising, an MIT team uses machine learning to hunt for new ingredients across the scientific literature.
Read More“IntersectionZoo,” a benchmarking tool, uses a real-world traffic problem to test progress in deep reinforcement learning algorithms.
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