Professor Ong Yew Soon and Dr Lim Keng Hui provide their insights on how artificial intelligence technologies can be applied to meet sustainability demand
Copyright: sustainabilitymag.com – “Sustainability applications for artificial intelligence”
The environmental impact of AI
The field of AI is progressing by leaps and bounds, driven by advances in hardware and an exponential increase in computing power. But the massive computation required to obtain these impressive technological feats comes at a price. Training AI models can incur substantial financial and environmental costs due to the energy needed to perform such computations. On top of the monetary costs of hardware, electricity and cloud compute time, powering such hardware for weeks and months at a time could also leave a huge carbon footprint.
Studies have found that Google’s AlphaGo Zero – the AI that plays the game of Go against itself to self-learn – generated a massive 96 tonnes of carbon dioxide over 40 days of research training. That is comparable to 1,000 hours of air travel, as well as the carbon footprint of about 10 average Singaporeans over an entire year.
In Singapore – a popular regional hub for data centres – there is growing concern over the increasing power consumption and widening carbon footprint of its data centre industry. A typical 20MW data centre on the island consumes the same amount of electricity a day as around 60,000 households – or about the energy usage size of Yishun town in Singapore. With an estimated 60 data centres here accounting for about 7 per cent of the country’s total electricity consumption in 2020, the carbon footprint is significant. […]
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Der Beitrag Sustainability applications for artificial intelligence erschien zuerst auf SwissCognitive, World-Leading AI Network.
Source: SwissCognitive