Machine learning

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

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Machine learning to combat ocean plastic pollution

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Data-driven recycling: AI sorts through the waste

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School Learning and AI: Personalized Lessons and Real-time Corrections

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AI contributes to species conservation with TrapTagger

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AI set to revolutionize the study of animal behaviour

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