Re:It takes a lot of energy for machines to learn
by toomuchtodo on Wednesday December 30, 2020 @04:18PM
(#25586237)
As always, there’s nuance. You can schedule workloads, machine learning/training included, where the power is cleanest (low carbon). Google relies on electricitymap.org/Tomorrow to do this.
The more folks who elect to pick where to compute based on low electrical carbon intensity, the faster the grid turns over to clean generation. You must vote with your fiat. I encourage technologists to include this consideration in their workload scheduling requirements. Renewables are almost always cheaper than fossil generation as well.
https://blog.google/inside-google/infrastructure/data-center...
The more folks who elect to pick where to compute based on low electrical carbon intensity, the faster the grid turns over to clean generation. You must vote with your fiat. I encourage technologists to include this consideration in their workload scheduling requirements. Renewables are almost always cheaper than fossil generation as well.