this post was submitted on 14 Sep 2026
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Data centers use evaporative cooling, not closed loop. You can't really scale up in a closed loop system. Evaporative utilizes a ton of water.
As for point 3, supercomputers have been assisting with scientific problems for decades now. This isn't new, just new tech applied. Your article is actually the best way to use AI, imo. It will be better at finding patterns in data than humans will ever be.
But my point is to say would it have been able to discover that those math problems existed in the first place?
No. The answer is no.
Yes you can obviously use a closed loop system and scale up? it's even becoming the standard? https://datacentremagazine.com/news/how-closed-loop-cooling-is-reshaping-data-centre-design
That is a massive goalpost shift. You went from can't do anything useful to couldn't have discovered the problems in one step?
Why does it even matter if it can't discover the problems if it can solve them, exactly? And why could it solve the problems and not discover new ones?
Closed loop isn't viable for data centers.
Do me a favor and quote my original text where I said they can't do anything useful. I'll wait.
Ftfy. If it's a penny more, which it is, corporations will do the less responsible "beholden to the shareholders" bullshit every time.
done.
also, the closed loop point is just false read my article?
How do you get "it isn't useful" out of that? If you have to extract a wild interpretation out of what (I thought) were pretty clear words, your argument isn't as strong as you think it is.
And yes, I read the article. It's speculative for existing data centers, which are the problem. There's no incentive for them to spend the money to switch to closed loop.
New data centers aren't incentivized to go that route either aside from the environmental impact. It would be nice if they were, though.
It can perform necessary tasks that actually drive intelligence and isn't derivative. See: those proofs.
You're essentially arguing that it's useless and just moves data around, this isn't true.
You're a little too caught up on that specific wording.
I never said or implied that it's useless. You're deriving meaning where there is none. It's a tool and tools are always useful. Here's an example of a supercomputer (not AI) designed to solve unresolved mathematical equations and scientific problems
Same idea, doesn't need AI to do it.
My point was, and is, that it cannot replicate human intelligence and that it doesn't have intelligence on its own.
Give an example of a problem a human can solve that an llm could not, then.
I’m not the guy you’re arguing with, but it will be interesting to see if/how LLMs deal with novel Gödel sentences in a way that is more than just mimicry. I’m sure there is a way to set this up that is mathematically rigourous.
The idea is that there are some statements which are true but unprovable in a formal system. Since LLMs run on a computer they are technically a formal system of sorts. So it will be interesting to see if they can pinpoint the true yet unprovable sentences. If they can it will lead to a lot of interesting questions about how exactly they know it’s true without “proving” it in some roundabout way.
I’m not doing this issue justice. A lot has been written on this by Roger Penrose (you don’t have to agree with his stance to appreciate that he’s touching on an interesting problem, here).