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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[–] oldjar7@alien.top 1 points 10 months ago

No and it's just a dumb argument. In Microsoft's presentation just a few days ago, they revealed they were planning on running their data centers on completely renewable energy. The fair comparison here is how much resources it takes to raise a person until the age of 25 where they start to contribute to society. And it's also what proportion of these people are actually creating new knowledge which is what we expect these models to be able to do? It's a very small proportion.