Social media neural networks could exhaust global energy supply

Advertising systems on platforms like Facebook and Twitter are like an energy ‘black hole’, according to new research. 

Researchers at the University of Copenhagen have been investigating the carbon footprint – and energy demands – created by artificial neural networks, the likes of which are used by social media platforms to recommend content based on user preferences. The results point to a ‘power black hole’, with experts recommending further development in this area should focus on more useful sectors than advertising and promotion.

The study shows networks are so complex and energy intensive, with significant emissions as a result, it would theoretically be possible for every energy source on Earth to be depleted before any neural network could be considered ‘perfect’. Essentially, an immeasurable amount of power will be used to progress in field in the coming years. 

‘The problem is that an infinite amount of energy can be used to, for example, train these neural networks just to target advertisements at us. The network would never stop training and improving. It’s like a black hole that swallows up whatever energy you throw at it, which is by no means sustainable,’ said Mikkel Abrahamsen, assistant professor at the University of Copenhagen’s Department of Computer Science. 

‘It’s important for us to consider where to use neural networks, so as to provide the greatest value for us humans. Some will see neural networks as better suited for scanning medical imagery of tumours than to target us with advertising and products on our social media and streaming platforms,’ he continued. 

In related news, a new series of artworks has been produced by the University of Bristol, designed to visualise and improve understandings of the future of energy systems.

Image credit: JJ Ying