So, if I understand this correctly, a few individuals in the USA are buying up all the RAM and GPUs being manufactured in the world, with huge loans that they are hoping they will be able to pay off someday, to put into some of the biggest data centers ever constructed, all over cheap, peaceful villages, for which the electric grid has to be substantially upgraded, massively increasing our carbon emissions, and a large portion of the available fresh water supply has to be redirected, so that we can consume:
- Generative AI: A Large Language Model (LLM) that has gobbled up most of humanity’s literature and content on the Internet, so that it can predict the next word in a sentence.
- Agentic AI: A list of traditional IF THEN statements that do things based on the output of the magical LLM and then create a new prompt that they feed back into the LLM in a never ending loop, with the aim of consuming as many tokens as possible.
- Ontology: A long list of relationships between real-world objects and concepts to constantly remind the LLM not to make up impossible stuff.
Correct?
I suspect that they have run out of ideas how to make us buy new smartphones.
The fresh water thing is wrong. The study that came out showing AI using shittons of water was including the cooling pond water at power plants. It was… 76% of the water use? I forget the % but it was so much that it completely changed the statistic from “holy shit” to “oh, who cares, then?”
Also, most of the mega huge data centers under construction are everywhere. Not “villages”. Meta’s big one is actually in the middle of nowhere.
Agentic AI isn’t just “if else” stuff. It’s way TF more complicated than that. It’s so fucking complicated, they’re terrified of implementing it at my work because they fear they won’t be able to understand what went wrong when something inevitably goes wrong (LOL).
The ontology thing isn’t really a thing. That’s just what outsiders are calling some internal programming they’re adding to LLMs so they don’t hallucinate “obvious shit”. The actual issue there is that, yeah: You can feed the LLM output back into itself four fucking times over to double-check it but that uses 4x as many tokens!
The thing you’re missing is that token usage is exploding. It’s like the world of AI has collectively decided that it needs that 4x token usage but they can’t figure out a way to do that economically, so they’re just sort of whistling while looking away from their balance sheets while at the same time getting seemingly endless loads from private equity idiots who think “AGI is just around the corner.”
ok. well in memphis elon is using 5 million gallons a day of fresh aquifer drinking water and then dumping it in the mississippi river.
he told the city that he would build a water treatment plant for his own use to curb the waste of drinking water.
he then ‘paused’ the building of the plant (still in its plannning phase) and instead is building more computer warehouses for grok.
please do not use grok.
I don’t know that story, but if the data center isn’t built yet, that’s just the normal water consumption that would be required for any building construction.
Building big buildings uses a lot of water. It’s necessary for dust management, soil compaction, etc. They literally just spray it everywhere during construction and that’s actually very important! LOL.
It always amuses me when I see people complaining about data centers that are still under construction using “millions of gallons” of water. I’m thinking, “yeah dude, that’s how construction works.”
They never complained about the construction water usage of all the other buildings in the area which make the “huge data center” look like a drop in the ocean for that kind of thing.
well setting your patronizing tone aside, it is not under construction. it’s the multiple colossus sites in memphis. elon has been running diesel turbines to power it for over a year.
and he’s using aquifer water to cool it.
maybe stop being an ass and read up on these things before correcting people who live next to this bullshit.
Thanks, interesting thoughts. I am trying to understand agentic AI and its potential uses and security risks better. I am also a bit hesitant to let it loose on my laptop, even if you sandbox the thing. I was also amazed how all our executives were pushing us to use AI for everything, without really trying to figure out legitimate use cases that will move the needle and without considering the massive potential costs. Then some of our agents suddenly got switched off, when token budgets were used up faster than expected.
The S in “agentic” stands for security!
I almost forgot: The reason why “business leaders” want to see AI everywhere is because they think it’ll be just like the adoption of every other technology to this point: It gets cheaper over time (not always better, but usually so).
The assumption is that if they “beat their competitors” to be the first ones using AI efficiently, they’ll utterly destroy them (economically; they won’t be able to compete). It’s a very bad assumption.
So far, “Big AI” is getting better but at costs that scale geometrically with the amount of “better”. That is: You can improve reliability (e.g. reduce hallucinations, increase accuracy, improve outputs in various ways, etc) but only by drastically inflating the cost and at reduced speed and efficiency.
We’re starting to learn that LLMs need about two generations of hardware advances before they’re going to be cost efficient for the types of “human productivity enhancement” that business leaders want. It’s only affordable now because “Big AI” is subsidizing the costs, trying to get customers hooked. The assumption being that if they’re hooked on AI, they’ll be able to raise prices to reflect actual costs. Just like the business leaders, this is a very bad assumption.
Instead, what’s going on is that the open weights AI models are starting to get “good enough” for most tasks (that you’d want to use them for, e.g. coding or agentic automation stuff). That means that all the billions and billions being spent by Big AI is just building up debt that will never be repaid and having this side effect of using up all the chip/memory capacity in the entire world.
It’s an absurd situation and the world will eventually look back on this time like we do the dotcom era.