Social media neural networks could deplete the world’s energy supply

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Advertising systems on platforms like Facebook and Twitter are like an energetic “black hole,” according to a new study.

Researchers at the University of Copenhagen have studied the carbon footprint – and energy demands – created by artificial neural networks, 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 that further developments in this area focus on more useful areas than advertising and promotion.

The study shows that the networks are so complex and power-intensive, with large emissions as a result, that it would theoretically be possible for every energy source on Earth to be depleted before a neural network could be considered “perfect”. Essentially, an immeasurable amount of power will be used to advance in the field in the years to come.

“The problem is that an infinite amount of energy can be used, for example, to train these neural networks just to target us with advertisements. The network would never stop forming and improving. It’s like a black hole that swallows up all the energy you send to it, which is by no means sustainable,” said Mikkel Abrahamsen, assistant professor in the computer science department at the University of Copenhagen.

“It is important for us to determine where to use neural networks, in order to provide the greatest value for us humans. Some will see neural networks as better suited for scanning medical imaging of tumors than for targeting us with advertising and products on our social media and streaming platforms,” he continued.

In addition, a new series of artworks has been produced by the University of Bristol, designed to visualize and enhance understanding of the future of energy systems.

Image credit: JJ Ying

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