Want to support ex-Google DeepMind members on their open-source projects to combat global warming
Jack Kelly, a retired DeepMind employee, started open source a machine learning project to fight global warming.
I am wondering if Team AI can help with spreading information through events.
See the master plan for the great initiative below.
I left Google DeepMind to build a non-profit research lab focused on helping to fix climate change ASAP. Very open and collaborative. Everything open-source. Focus on practical, scalable interventions, starting with forecasting solar PV. (Twitter)
First product: Current projections for solar PV (hours ahead)
Solar power generation is the largest source of uncertainty for national grid projections.
As dark clouds move across the sky, the grid is taken with surprise and can lose hundreds of megawatts of solar power within minutes.
This lost solar must be replaced immediately. But thermal generators take hours to recover from the cold.
As a result, whenever the sun shines, the National Grid maintains a large amount of rotational reserve online. Most of them are gas turbines, which maintain idling but do not generate electricity. It is economically expensive and carbon-intensive.
If PV predictions improve over the next few hours, the grid will be less ready to rotate. In other words, better PV projections will reduce CO2 emissions and save money.
In the United Kingdom, better PV projections range from £1 to 10 million per year (Taylor et al., 2016), and 100,000 tonnes of CO for 2 per year (see Appendix).
On a global scale, carbon savings will be in the order of tens of millions of tons per year.
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