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This is a problem, and one which is only going to grow.
EMEA Director, HPC & AI at Lenovo Infrastructure Solutions Group (ISG).
Every new generation of models requires more computing power for inference, and more energy to train.
Its a constant cycle that continually adds demand onto the requiredinfrastructure.
Todays GPUs can consume up to 700 watts, and an average installation takes eight GPUs perserver.
So, the big question is, how can we make this more sustainable?
But small steps can make a big difference.
The computing industry is being sent a loud, clear message to create better products that use fewer resources.
This call is coming from consumers and investors, but also increasingly from governments.
Being energy efficient will in future be a legal requirement for organizations in the AI space.
Data centers driven by renewable energy sources will be key to reducing AIs carbon footprint.
This raises questions around whether we should view those different energy demands differently.
It is certain that AI has enormous potential to do good, already having an impact in many areas.
Used responsibly, AI can go hand in hand with sustainability objectives.
As the world comes together to drive towards net-zero, AI will increasingly play an important part.
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