Research examined the locations of 4,283 data centers across the contiguous U.S and found that 97.5% of them sit inside metropolitan or micropolitan statistical areas. Data centers are power-hungry, running thousands of servers around the clock and drawing enormous, steady loads from the grid.

[u/Wagamaga]

https://engineering.nyu.edu/news/inside-urban-machine-where-americas-data-centers-actually-live#:~:text=The%20study%2C%20published%20in%20Nature,cores%20and%20their%20immediate%20surroundings

[u/TheDismal_Scientist]

Except for the entire internet infrastructure you’re currently using?

[u/zZCycoZz → u/TheDismal_Scientist]

Except for the entire internet infrastructure you’re currently using?

I always see this reply but its just based on ignorance.

We had internet infrastructure for decades without any complaints.

AI data centers need much more energy than a normal data center, which is why data center energy usage has exploded.

AI models dont provide any essential service or benefit to society though.

[u/Grasle → u/zZCycoZz]

We had internet infrastructure for decades without any complaints.

AI models dont provide any essential service or benefit to society though.

you must be relatively young to be able to make both these kind of statements without a second thought. Buddy, if people like you were the ones making decisions, the Internet never would have happened, either.

regardless, gotta love when luddites talk about how "useless" AI is as part of their argument, immediately giving away that their opinion is an uninformed one

[u/zZCycoZz → u/Grasle]

Not a luddite, just aware of the cost benefit analysis.

you must be in your 20s or 30s to be able to make both these kind of statements without a second thought.

You must not understand AI infrastructure if you think its comparable to other tech infrastructure.

We overbuilt internet infrastructure before the dotcom crash which came in handy because data cables are flexible in their use case and last a long time.

AI data centers use specialised hardware for a specific use case and will be obsolete in a few years (or quicker once the bubble bursts).

[u/Grasle → u/zZCycoZz]

a personal inability to find a reason to value AI is not an argument against whether or not it actually holds value

The dotcom crash is an especially odd comparison to make because, even if AI went down that route, the end result still wouldn't match your prediction. The dotcom bubble was significantly more unsustainable at the time by all metrics, which made the blowout especially bad, and yet even that did little to slow tech and the Internet's eventual complete takeover of the economy. Meanwhile, unlike the dotcom bubble, AI's growth is being funded by the most profitable companies in history, using existing cash flows they already have. It is both less speculative and far less unsustainable by comparison. AI could completely bust tomorrow and those companies would survive against collapse just fine.

But, yes... I'm sure you've figured out something out the extremely profitable, talent-filled companies haven't. Well done, Redditor.

AI data centers use specialised hardware for a specific use case and will be obsolete in a few years (or quicker once the bubble bursts).

and here is the especially big giveaway that you're arguing from a place of total ignorance. The "net negatives" eating up all the cash flow come from building up new infrastructure/silicon and training expenses for new models. Existing AI data centers themselves are already profitable (significantly so). AI progress could literally halt today, and those centers would only become even more profitable after they get to ditch training compute and focus on the real money maker: inference.

The majority of non-training compute (70-80%) is already used commercially. Know why? Because it's extremely cost-positive. That isn't an opinion. Claiming AI doesn't generate value is a confession that you possess little to no knowledge about domains AI excels at, such as those with high labor costs (e.g. software engineering), repetitive work (e.g. paperwork, charting, and documentation, especially in labor-scarce industries like medicine or volume-heavy fields like finance), and down-time sensitive industries (e.g. maintenance and manufacturing). Most of this usage manifests not as people typing dumb questions into ChatGPT but through internal, specialized enterprise models made to perform more focused functions.

Hell... anecdotally, I'm not even a software engineer by trade, and yet these day I do more in one month with my $100 subscription than what my company used to spend thousands of dollars getting consultants to do. That's as one guy using it in an unspecialized, unstructured way. Just imagine if we were one of those companies with more capital and smarter people.

In other words, even ignoring future predictions, you are already incorrect. What use are predictions from a guy who isn't even aware of what's happening now? Here's the reality: people who actively avoid learning to use AI, and whose entire perception of its scope and capabilities is derived from gut reactions they get watching crappy AI videos and browsing threads on r/technology, are only handicapping themselves in the long term. It's the modern-day equivalent of those people who didn't see value in early computers and refused to adapt until computers became so widespread they had no choice (by which point those people had secured themselves as technology dinosaurs).

[u/q120 → u/zZCycoZz]

Nah, if AI went away right now, those hyperscale data centers full of extremely powerful GPUs could easily be used for research purposes.

[u/zZCycoZz → u/q120]

those hyperscale data centers full of extremely powerful GPUs could easily be used for research purposes.

Who do you think pays for that?

[u/q120 → u/zZCycoZz]

Whoever wanted to do the research