911
Before and after data centers
(discuss.online)
Original comment: https://www.reddit.com/r/interestingasfuck/comments/1uyyywv/comment/oy3cgd7/
Trees vs. Data Centers
Photo 1: Memphis, TN (top)
Photo 2: Sandston, VA
Photo 3: Abilene, Texas
Photo 4: New Albany, OH
Photo 5: Fayetteville, GA
Things need space to be built, but all of those other things you mentioned have value. It's upsetting to cut down a shitload of trees for something that is going to be useless in 3 years when the AI bubble pops.
AI isn’t ever going away. It’s here to stay like cars, houses, the internet. It’s part of life as we know it, and it’s literally never going to disappear.
You think the world is just going to go back to normal LLM usage?
People still have houses and mortgages after the mortgage bubble burst in 2007.
The internet, ecommerce, and .com's still exist after the dot com bubble burst in the early 2000s.
A bubble bursting doesn't mean that thing dies and goes away. It means that the hype for it goes away and the market normalizes/corrects suddenly.
There's a VC run and an attempt to force AI usage into things where it doesn't belong, or serves no purposes, or completely alienates the user base. There is going to be a correction for sure, and its not going to be pretty.
No, people genuinely think AI is going away because it’s “useless” and doesn’t provide anything worthwhile. The comment I replied to said the AI data centre will be useless when the bubble bursts. If they don’t think AI will go away, why would they say that?
I'm anticipating that mixed-use data centers will have enough capacity to meet post-pop demand. The current ubiquity of LLMs will end once people are forced to pay the true cost. I don't expect the technology to suddenly just vanish, but most people are not going to be willing to pay what it will cost to make inference profitable.
Demand isn’t going to reduce though. It’s going to continue increasing.
That depends heavily on the quality bar, not just aggregate capacity. Gemini 3.5 Flash qualifies on 42 of 52 tasks at a 75% bar, but only 15 at 100%—so routine workloads may remain cheap while demanding ones become premium. The real question is how much of today’s usage needs near-perfect output.