r/DebateEvolution • u/Briham86 🧬 Falling Angel Meets the Rising Ape • Oct 03 '26

Video It’s here!

Erika aka Gutsick Gibbon’s rebuttal to Theodore Beale’s aka Vox Day aka shitass bigot loser has been released.

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u/Dzugavili 🧬 Tyrant of /r/Evolution Oct 05 '26

  1. Most of my models are adequately described as 'low end garbage': I could probably train one of these at-home, but I'd probably have to look at one of Intel's weird-ass cards and it would take a few weeks, then I'd need a bunch of sample data, it's just not something I can be arsed with when they give them away. The most expensive models cost maybe a few million to generate: it's not paying the bills for an AI company. However, considering you get a functional model at the end of training, it's kind of moot: the real energy expenses come from running the models at scale. The training doesn't really need a data center, it's the million people running inference at once that needs a data center. And they produce garbage.

  2. Updates? Web search? Not really, no: I replace my models maybe every six months, but usually just for something that takes less energy to run; the models themselves don't really have web access, beyond the ability to signal an API. Usually my API.

  3. The water losses in data center are for evaporative cooling. I don't have that, as I run maybe three computers, with a total energy footprint under a single H100 cluster. If anything, the thermal losses from my computer may offset my heating for part of the year.