From cleaning up city transport systems to bringing transparency to supply chains, AI and deep learning have the potential to transform sustainability

If killer robots and mass unemployment represent a dystopian future for an AI world, then speeding sustainability is a much more palatable one. And there is no shortage of opportunities on the menu.

DeepMind has earned its spurs for Google by using machine-learning to cut energy consumption in its cooling centres by up to 40% - and that’s starting from a very high base, as Google was already famously energy-efficient. As well as making inroads into Google’s own consumption, it will also help cut energy use among companies that run on its cloud.

Although other such applications are only just crawling out of the sandbox, experts are excited about the wider potential of AI, as part of the “fourth industrial revolution” (4IR), to make a step-change in sustainability. In its report, Innovation for the Earth, PwC identifies a number of ways in which 4IR tech offers “substantial potential to move towards a zero-net-emissions economy”.

Farming would benefit, with remote monitoring spotting any sign of crop disease, anticipating impending droughts, checking soil fertility, and triggering interventions as soon as required

PwC paints a picture of a world...

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DeepMind  google  PwC  Industry 4.0  sustainable cities  SDGs  UN Global Pulse  agri-tech  medicine  IoT  AI for good  Big data 

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