In my masters degree I always ran many computations as did all my peers
The reality is that more of us are than not are using huge HPC clusters / cloud computing for many hours on each project
The industry is just GPUs going BRRR
I’m wondering if this has potential implications for ML in society as AI/ML becomes more mainstream
I could see this narrative being easily played in legacy media
Ps - yeah while there are researchers trying to make things more efficient, the general trend is that we are using more GPU hours per year in order to continue innovation at the forefront of artificial inference
Why not just do an environment tax on every kWt/h produced and then use that environment tax money to fix the environment?
I.e. if burning 1 kg of coal produces 1 kWth of energy and costs 1$, but it costs 10$ to extract 1 kg of coal from the air in the form of CO2, just put a tax on it and make every 1 kWth of coal energy cost 11$ instead.
That way, clean energy is cheaper and more attractive, and dirty energy costs what it truly costs, i.e. the harm to the environment is quantified.