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Reducing the Carbon Footprint of AI


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The researchers system trains one large neural network comprising many pretrained subnetworks of different sizes that can be tailored to diverse hardware platforms without retraining.

A new automated artificial intelligence system for training and running certain types of neural networks has a relatively small carbon footprint.

Credit: MIT News

Massachusetts Institute of Technology (MIT) researchers have developed an automated artificial intelligence (AI) system for training and running certain types of neural networks, which has a relatively small carbon footprint.

The researchers built the system via automated machine learning, which trained the OFA network.

Using the system to train a computer-vision model, the researchers calculated that the effort required approximately 1/1,300th the carbon emissions of modern state-of-the-art neural architecture search strategies, and reduced the duration of inference by 1.5 to 2.6 times.

MIT's John Cohn said, "The upside of developing methods to make AI models smaller and more efficient is that the models may also perform better."

From MIT News
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Abstracts Copyright © 2020 SmithBucklin, Washington, DC, USA


 

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