• SpacetimeMachine@lemmy.world
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      6 months ago

      FSR in this case doesn’t need to be trained more. It’s already a complete dataset, so now it can be released to run on MILLIONS of devices and reduce their load. And then you knock railroads which are one of the most efficient forms of land transportation we have. Just full of bad takes here.

    • doggle@lemmy.dbzer0.com
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      6 months ago

      Training an AI is intensive, but using them after the fact is relatively cheap. Cheaper than traditional rendering to reach the same level of detail. The upfront cost of training is offset by the savings on every video card running the tech from then on. Kinda like how railroads are expensive to build but much cheaper to operate after the fact.

      It’s pretty simple. If you can’t understand delayed gratification, then you’re right: school did fail you.

      Ps.: the railroad comparison really breaks down when you consider that they’re cheaper to build than the highways that trucks use and that we don’t, in fact, need to truck in the resources anyway. We’ve been building railroads longer than trucks have existed, after all.

      • meseek #2982@lemmy.ca
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        6 months ago

        Thanks for the totally made up figures. I’m glad we agree that training itself is quite costly. No data on how much energy AI will save vs rendering (as we don’t know how much we can avoid rendering; there has to be a cap) so can’t really keep riding that horse.

        You’re right tho, the rail analogy sucks. Not for the reasons you list tho, but rather because they will never stop training AI. Unless you feel AI will stop learning and needing to evolve.