this post was submitted on 16 Nov 2023
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Machine Learning

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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

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[–] Gnaeus-Naevius@alien.top 1 points 11 months ago

Not going to get into a big debate on this one ... but the market cap of bitcoin is $1.44 Trillion at the moment. Where did this "wealth" come from? Well from nothing, and it can't be converted into anything physical or otherwise useful, so it is the currency aspect only. I don't have recent numbers, but around 2022, the network was using 131.26 terawatt-hours of electricity annually. No idea what the cost is in terms of hardware and labour misallocation. That is an insanely inefficient decenstralised currency, so extremely unlikely to be a net positive.