Emissions
Emissions

Emissions

Alternative energy Artificial Intelligence Chemical engineering DMSE Electrical engineering and computer science (EECS) Emissions Energy Energy efficiency Faculty Laboratory for Information and Decision Systems (LIDS) Lincoln Laboratory MIT Energy Initiative Renewable energy School of Engineering Special events and guest speakers Staff Sustainability

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.

Artificial Intelligence Civil and environmental engineering Cleaner industry Concrete Concrete Sustainability Hub DMSE Emissions Environment Infrastructure Materials science and engineering Research School of Engineering Sustainability Technology and society

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.

Algorithms Artificial Intelligence Autonomous vehicles Civil and environmental engineering Computer science and technology Data Emissions IDSS Laboratory for Information and Decision Systems (LIDS) Logistics machine learning MIT Schwarzman College of Computing Research School of Engineering Sustainability Traffic management Transportation

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.

Artificial Intelligence Civil and environmental engineering Climate change Collaboration Emissions IDSS International initiatives Mechanical engineering MIT Schwarzman College of Computing MIT Sea Grant Nuclear science and engineering Oceanography and ocean engineering Research School of Engineering Supply chains Technology and policy Transportation

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.

Algorithms Alumni/ae Artificial Intelligence Civil and environmental engineering Cleaner industry Climate change Computer science and technology Emissions Energy Graduate, postdoctoral IDSS machine learning Profile School of Engineering Students Sustainability Traffic management Transportation Undergraduate Research Opportunities Program (UROP)

Puzzling out climate change

Accenture Fellow Shreyaa Raghavan applies machine learning and optimization methods to explore ways to reduce transportation sector emissions.

Alumni/ae Artificial Intelligence Cleaner industry Emissions Energy efficiency Industry Innovation and Entrepreneurship (I&E) machine learning MIT Sloan School of Management real-estate Renewable energy School of Architecture and Planning Solar Startups Sustainability Wind

A platform to expedite clean energy projects

Station A, founded by MIT alumni, makes the process of buying clean energy simple for property owners.

Artificial Intelligence Chemical engineering Cleaner industry Climate change Data Electricity Emissions Energy MIT Energy Initiative Nuclear power and reactors Renewable energy School of Engineering Sustainability Sustainable computing Technology and policy Technology and society

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.

Algorithms Artificial Intelligence Cleaner industry Climate Computer Science and Artificial Intelligence Laboratory (CSAIL) Computer science and technology Data DMSE Electrical engineering and computer science (EECS) Emissions Energy Environment Human-computer interaction machine learning MIT Schwarzman College of Computing School of Engineering Sustainability Sustainable computing Water

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.

Artificial Intelligence Climate change Computer science and technology Electricity Emissions Energy Energy efficiency Interview Lincoln Laboratory machine learning Staff Supercomputing Sustainability Sustainable computing Technology and society

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.

3-D printing Algorithms Alumni/ae Artificial Intelligence Chemical engineering Cleaner industry Climate change Design Emissions Innovation and Entrepreneurship (I&E) Interview machine learning MIT Morningside Academy for Design Pollution Product design School of Architecture and Planning School of Engineering Startups Sustainability The Engine

Q&A: A blueprint for sustainable innovation

Atacama Biomaterials, co-founded by Paloma Gonzalez-Rojas SM ’15, PhD ’21, combines architecture, machine learning, and chemical engineering to create eco-friendly materials.