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Sixteen new START.nano companies are developing hard-tech solutions with the support of MIT.nano

Startup accelerator program grows to over 30 companies, almost half of them with MIT pedigrees.

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Decoding the Arctic to predict winter weather

With the help of AI, MIT Research Scientist Judah Cohen is reshaping subseasonal forecasting, with the goal of extending the lead time for predicting impactful weather.

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How artificial intelligence can help achieve a clean energy future

AI supports the clean energy transition as it manages power grid operations, helps plan infrastructure investments, guides development of novel materials, and more.

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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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Making climate models relevant for local decision-makers

A new downscaling method leverages machine learning to speed up climate model simulations at finer resolutions, making them usable on local levels.

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MIT-derived algorithm helps forecast the frequency of extreme weather

The new approach “nudges” existing climate simulations closer to future reality.

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Generative AI for smart grid modeling

MIT LIDS awarded funding from the Appalachian Regional Commission as part of a multi-state collaborative project to model and test new smart grid technologies for use in rural areas.

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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.

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Detailed images from space offer clearer picture of drought effects on plants

J-WAFS researchers are using remote sensing observations to build high-resolution systems to monitor drought.