Guest essay by Eric Worrall
A Google project to use artificial intelligence to improve the predictability of wind energy appears to have failed. Engineers who worked on the project have reportedly removed mention of their work from their linked in profiles.
Climate change falls down the agenda at A.I. lab DeepMind after energy heads leave
- The DeepMind Energy unit, which has attracted its fair share of attention over the years, has vanished and none of the company’s staff mention it on their LinkedIn profiles.
- At one point, DeepMind wanted to use its AI technology to optimize National Grid, which owns and operates the infrastructure that provides electricity to homes and businesses around Britain.
- The organizations spent a considerable amount of time working together, but there were many hurdles to overcome if anything was ever going to be implemented.
LONDON — Artificial intelligence (AI) lab DeepMind has shifted its focus from climate change to other areas of science and is pursuing its original mission of creating artificial general intelligence (AGI), which is widely seen as the holy grail of the nascent technology, according to several people familiar with the matter.
One of the DeepMind’s early and perhaps most successful projects involved slashing Google’s enormous electricity bill, instantly reducing the company’s carbon footprint. The search giant, technically a sister company to DeepMind as they’re both run by Alphabet, announced in July 2016 that it had been able to reduce the energy consumption of its data center cooling units — used to stop Google’s servers from overheating — by as much as 40% with the help of a DeepMind AI system.
While the company’s achievements are significant, it has yet to publicly confirm where and how its energy-saving AI has been applied beyond Google’s data centers and wind farms.
National Grid nightmare?
At one point, DeepMind wanted to use its AI technology to optimize National Grid, which owns and operates the infrastructure that provides electricity to homes and businesses around Britain.
“We’re early stages talking to National Grid and other big providers about how we could look at the sorts of problems they have,” DeepMind Chief Executive Demis Hassabis said in an interview with The Financial Times in March 2017. “It would be amazing if you could save 10% of the country’s energy usage without any new infrastructure, just from optimisation. That’s pretty exciting.”
Last March, it emerged that talks had broken down between DeepMind and National Grid. The organizations spent a considerable amount of time working together, sometimes at a National Grid facility near Reading, in the English county of Berkshire, but there were many hurdles to overcome if anything was ever going to be implemented.
Gary Marcus, CEO of robotics company Robust AI, and co-author of “Rebooting AI,” which critically analyzes the industry and suggests how to advance it further, told CNBC that the technology may not have worked well enough for National Grid to justify the cost.
“Their primary technique, deep reinforcement learning, works best in well-controlled environments, such as board games, and may struggle with the complexity and unpredictability of the real world,” Marcus told CNBC.
Sheikh added: “The technology might not have worked because it’s not really that mature.”
This is not the first time a high profile Google renewable energy project failed.
Back in 2016 Google Engineers announced the failure of an engineering project to find a feasible path to 100% renewable energy. The 2016 project Google engineers concluded renewable energy “simply won’t work”.