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Taming AI models to minimize their impact on climate

● A researcher and machine-learning specialist at the University of Copenhagen, Raghavendra Selvan explains AI’s runaway energy consumption and what can be done to keep it under control.
● Having developed methods to measure the carbon footprint of machine-learning tools, Selvan aims to improve AI models to limit their impact on climate.
● Redesigned processing hardware as well as optimized software and software training can contribute to the drive to build high-performance AI tools with lower energy needs.

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Keeping watch on the carbon footprint of machine learning

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Dreamwaves: augmented reality with virtual 3D-sound to help guide the blind

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Data-driven recycling: AI sorts through the waste

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Machine learning to combat ocean plastic pollution

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Green and Local Energy Exchanges and Optimizing Network Consumption

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VR occupational training gains traction at Laval Virtual trade show

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Innovation is also here

Generative AI product landscape continues to evolve

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A new router for Enedis transformers across France

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The solution to EX, CX and OX? Solve X by focusing on why

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