Energy efficiency
Energy efficiency

Energy efficiency

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.

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Collaborating to advance research and innovation on essential chips for AI

Agreement between MIT Microsystems Technology Laboratories and GlobalFoundries aims to deliver power efficiencies for data centers and ultra-low power consumption for intelligent devices at the edge.

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A platform to expedite clean energy projects

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

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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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Want to design the car of the future? Here are 8,000 designs to get you started.

MIT engineers developed the largest open-source dataset of car designs, including their aerodynamics, that could speed design of eco-friendly cars and electric vehicles.

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AI pilot programs look to reduce energy use and emissions on MIT campus

A cross-departmental team is leading efforts to utilize machine learning for increased efficiency in heating and cooling MIT’s buildings.

Artificial Intelligence Computer science and technology Electrical Engineering & Computer Science (eecs) Electronics Energy efficiency Invention Light machine learning Materials Research Laboratory National Science Foundation (NSF) Photonics Research Research Laboratory of Electronics School of Engineering

Machine-learning system based on light could yield more powerful, efficient large language models

MIT system demonstrates greater than 100-fold improvement in energy efficiency and a 25-fold improvement in compute density compared with current systems.