Sustainable computing
Sustainable computing

Sustainable computing

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.

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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.

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Startup accelerates progress toward light-speed computing

Lightmatter, founded by three MIT alumni, is using photonic technologies to reinvent how chips communicate and calculate.

Algorithms Artificial Intelligence Computer Science and Artificial Intelligence Laboratory (CSAIL) Computer science and technology Data Electrical Engineering & Computer Science (eecs) machine learning MIT Schwarzman College of Computing Research School of Engineering Sustainable computing

Learning to grow machine-learning models

New LiGO technique accelerates training of large machine-learning models, reducing the monetary and environmental cost of developing AI applications.