Brain-inspired electronic system could vastly reduce AI's carbon footprint
https://www.sciencedaily.com/releases/2020/08/200827150957.htm
The system, which uses memristors to create artificial neural networks, is at least 1,000 times more energy efficient than conventional transistor-based AI hardware, but has until now been more prone to error.
Existing AI is extremely energy-intensive -- training one AI model can generate 284 tonnes of carbon dioxide, equivalent to the lifetime emissions of five cars. Replacing the transistors that make up all digital devices with memristors, a novel electronic device first built in 2008, could reduce this to a fraction of a tonne of carbon dioxide -- equivalent to emissions generated in an afternoon's drive.
Brain-inspired electronic system could vastly reduce AI's carbon footprint
Sep 2, 2020, 12:18pm UTC
https://www.sciencedaily.com/releases/2020/08/200827150957.htm
> The system, which uses memristors to create artificial neural networks, is at least 1,000 times more energy efficient than conventional transistor-based AI hardware, but has until now been more prone to error.
> Existing AI is extremely energy-intensive -- training one AI model can generate 284 tonnes of carbon dioxide, equivalent to the lifetime emissions of five cars. Replacing the transistors that make up all digital devices with memristors, a novel electronic device first built in 2008, could reduce this to a fraction of a tonne of carbon dioxide -- equivalent to emissions generated in an afternoon's drive.