A surge in new datacenters, each with the power demand of 100,000 households and a cooling water demand of 1,000,000 m³ per year to train AI models on material obtained without consent on hardware now unaffordable to consumers so fascism-adjacent tech billionaires can sell us the idea that any skill is now worthless and in doing so creating the largest economic bubble ever while simultaneously destroying society and environment.
I think that about sums it up.
@oli I have to disagree on one point: it takes surprisingly little hardware resources to run #GenAI efficiently for say 20 ppl. The hardware required for this is now quite affordable for a reasonably sized company as well as for enthusiasts (excluding the current crazy RAM prices). And decentralised operation neither requires a nuclear power plant nor an ocean for cooling, it works perfectly well with renewable energy.
Decentralisation is the key, one could perhaps even call it democratisation.
@oli @riaschissl I agree with you that pure parameter count is not what we're after but "a few rtx 6000" translates to roughly 30-40k + supporting hardware around it + electricity. That's nowhere near what 20 people would spend on AI subscriptions and the performance of the model you'll be running is simply worse - maybe by a lot maybe by a little, currently is by a lot but that could change soon
and in 5 years you would still have to buy new hardware, doing a similar (or bigger) investment.
I fail to see how that makes any kind of economical sense
@dzervas @oli take the cheapest Claude Max subscription for 100 per month, this sums up to 24k per year for 20 devs. And if you just take the ordinary team subscription, it's more than 7k per year. So the economical sense is there, plus not having to worry about what happens to your data.
And in a corporate environment, replacing hardware every 5 years is not unusual, if not the norm.
Oli
udo m. rader ☕ 🇪🇺 🇺🇦 🐧
Dimitris Zervas