And this is why you need a lawyer when you’re doing this kind of thing.
If this farmer was smart, there would be a clause in the contract that the land may only be used for a park or other public space. And that if the city decides to resell the land, the farmer or their descendants will have the right to reclaim it.
Thus, farmer could either stop the data center or at least get a solid payday.
The issue is heat. If your data center consumes 100 megawatts, that’s 100 megawatts of electricity that turns into 100 megawatts of heat. Part of the challenge of a data center is getting rid of that heat and keeping the servers cool.
There’s a fun little principle called latent heat in phase change. To take 1 g of water and heat it from just above freezing to just below boiling consumes about 100 calories of energy. To then boil it, to raise it just a fraction of a degree and turn it into steam, takes another 433 calories of energy. So if your data center has 100 megawatts of heat to get rid of, turning water into vapor is a great way to get rid of it.
You don’t actually even need to boil the water, if you take warm water and spray it into the air, some of it will evaporate and the water that comes back on the ground is significantly colder than what you sprayed in the air. This is harnessed with a machine called a cooling tower, it’s a big boxy thing that has a ton of little waterfalls and wet plates inside it while a giant fan blows tons of air through it. You pour warm water in, some of it evaporates, the water that comes out is much colder. Many buildings use this as part of their air conditioning system. But when that water evaporates, you need more water to replace it. And that’s why they say data centers consume water. The water isn’t destroyed, but it is released into the atmosphere as steam or humidity and thus is no longer usable until it rains again. Which, depending on your climate, may be sometime away or may be some distance away.
If it’s only good for 3 years, the economics are basically impossible.
Also consider that as models improve, the newer frontier models that are doing actual useful work require significantly more compute and RAM than basic chat bots…
I’m sure Bernie Madoff’s fund had an ‘accounting puzzle’ too.
I love how the publications call it a ‘puzzle’ rather than what it so obviously is- a bunch of people throwing $billions at tech they don’t understand which has no serious road to profitability anytime soon.
Here’s the problem… He says AI was adopted beyond his expectations. Great.
But if somebody is using it at the current price point of super cheap or free, are they going to keep using it when it gets expensive?
You can make a basic chatbot run on a desktop PC, but nobody wants to pay for that. Once you get into things with useful generation and large context windows, or things like video generation, suddenly you need one or more $10,000+ pieces of hardware to run it. So the $10 a month you charge the user is basically an introductory price that doesn’t cover your hardware fees let alone the software engineers to build your AI.
Eventually, the bill comes due. Eventually, you have to look at your customers and how much machine time they use each month and how much your r&d costs and figure out what the actual cost to the customer has to be. And then the customer rethinks how useful the AI is or isn’t.
People will pay $10 a month for chat GPT to write their emails. Will they pay $100 a month?
What about the company that replaced all their software developers with AI. Suddenly the AI cost as much or more as the software developers. Only now the developers who understood the code base work for other companies.
There will be a fun correction when this happens.
Quite true. The thing is, there aren’t billions and billions of dollars in chatbots. The billions are for the creative stuff and the code.
And that is where the reckoning / correction will come from, the bill has to come due eventually. When top end generative AI starts to have a real cost associated with it, then it’s no longer a blanket ‘everyone start using this immediately’ mandate, it prompts some consideration of cost versus output quality.
Not pop. Correct.
A lot of the managers aggressively pushing AI have little or no understanding of it themselves. They just hear of a technology that can make a human more productive by doing most of the work for them. So absolutely that’s worth a ton of money. It’s why many companies are encouraging if not demanding employees to start using AI- because in their mind, one employee fully utilizing AI can do the work of two standard employees. Of course they believe this because they’ve never actually had to use the damn thing themselves and thus don’t realize it doesn’t do all the work for you. Or worse they think it does and your wonderful code base turns into spaghetti.
Side note- A few companies even had leaderboards for who was using the most AI tokens. This led to ‘tokenmaxxing’, trying to consume as many tokens as possible to prove you are adopting AI. Things like 'Write unit tests for our company code base, then refactor the code base. Spin up an instance of Claude and another of ChatGPT to each generate unit tests of the old code and run them against the new code, then run the tests against each other to check each other’s work, submit full debug output to another instance of gpt 5.5 that will check for hallucinations… Keep that query going for a few paragraphs and you’ll have an army of AI workers all checking each other’s work while producing zero productive output but costing a fortune to run.
Ever run an AI model locally? If you want the most capability you need a fast GPU with 32-48gb RAM. And that’s all for you, ONE user.
Copilot has millions of users, with tens or hundreds of thousands of them hitting the AI all at once. Each one needs $thousands worth of GPU and RAM dedicated to them for the length of their query processing.
Where do you think the money to buy all that hardware comes from? You see OpenAI buying a double digit percentage of the world’s RAM production, you think they got it on clearance sale?
No, there are investors. Investors who are pouring hundreds of billions into this AI stuff. And they don’t do this because it’s fun, they do it because they expect a BIG return.
So what’s going on is just like your neighborhood drug pusher, only the drug pusher is more honest. He says ‘first hit’s free, man’. AI company says ‘AI models are an easy and cost effective way to modernize your workflow!’; they don’t tell you that once you’ve integrated them and fired all the humans who know how to do the work, the price is gonna go way up.
Because the fact is, there IS a real cost of AI compute. GPU time, or at the large scale, datacenter space, power, cooling, etc.
In another few months to few years, the C-suites will stop huffing the koolaid and will start doing cost-benefit analysis on where AI is and isn’t cost-effective vs. humans. With any luck (for the AI people) by that time the AIs will be good enough that it’s a clear benefit. If not this bubble’s gonna pop.
I think that was before. Now it’s based on the compute cost of the request. Like if you ask a large model to perform a long and difficult task you’ll pay through the nose. If you ask a simple model to perform an easy task it’ll be dirt cheap. And that’s what’s got people pissed, is that what used to be ‘one query’ now may consume a lot of credits and it may not be clear how many.
And let’s not forget- don’t listen to customers.
Do customers want a ‘Hero 47’ camera with a new one every year? Nope.
Do customers want to be pushed into a paid cloud video storage and editing system that can’t handle the camera’s full resolution? Nope.
Do customers want a reliable camera that has good battery life, doesn’t overheat or crash, and generally works as advertised? YES THEY DO!
So what should we do? Let’s release a new camera every year, with the same overheating and firmware bugs, and push people into a phone based video platform.
Now we don’t understand why Insta is doing so well…
They stopped selling an OK camera and started selling cameras that overheat in the shade with dark patterns to try and force you into using their mobile app for video processing.
make action cameras that people want to buy?
instead of pushing the same product with minor updates for greater costs which bring no benefit to the consumer?
They might try making cameras that don’t overheat and shut down after 10 minutes…
‘Book’? What is that?
Oh wait I heard about those, it’s a stack of cellulose pulp sheets with markings on them right?
I know some people say they are useful for something but I can’t imagine what, as nobody ever taught me how to read them.
Pass the milk?
This is horrible.
I really wish the government would release some kind of guidance or documentation on the safe processing and packaging of milk so this sort of thing could be prevented. Really a shame that nobody does anything here, these poor innocent people probably had no idea their milk might possibly be contaminated…
oh wait…
Sad, but not surprising. I like GoPro, their cameras are pretty nice. But they have not innovated well. And you look at actual users, and it’s the same complaints always- camera overheats, battery doesn’t last long enough, firmware bugs, unresponsive support.
Then look at the new darling, Insta. Their 360 camera is perfect for creators that don’t know what shot they are going to want.
It would be very sad to see GoPro bite the dust, but if they do they’ve no one to blame but themselves.
Yes exactly. If you need more total capacity you add more tanks, if you need more instantaneous output power you add more electrodes. And thus you can scale either one without messing with the other.
Here’s the short version.
A normal battery is a sealed cell. It has a positive and negative electrode, with an electrolyte between them. Usually many layers of this. When you charge it, a chemical change happens. When you discharge it, that chemical change is undone.
A redox flow battery uses fixed electrodes, but a liquid electrolyte that can be pumped and stored. This means you can increase overall storage capacity simply by adding more electrolyte tanks, without needing more electrodes. Think of it like a generator with a bigger gas tank.
The whole vanadium thing is just one of the metals used in the battery. There’s a few kind of redox flow batteries using different chemistries
Hmm Are you wedded to that particular Mac address? If not, shut down the VM, delete the virtual Network card, then make a new virtual Network card. Copy paste the Mac of that new card into pfsense with the static mapping, and fire up the VM. See what happens.
If that doesn’t work, I remember something it was possible for proxmox to do some kind of routed Network system. To investigate that, delete all static mappings, fire up the VM, and just look at what Mac address it shows getting the DHCP lease. Is it the one that shows as being assigned to the VM?
Yeah this still sounds very much like what I had happen. pfSense tries really hard to hang on to that old random dhcp lease sometimes.
Don’t worry about ARP- that just shows what currently exists.
You might try turn off the vm, delete the static mapping, then delete the DHCP lease in status - dhcp leases, then add the static mapping again and turn the vm back on.
Also on pfSense check /var/dhcpd/var/db/dhcpd.leases . Chances are your VM is in there. Turn off VM, stop DHCP service on pfSense, delete lease from that file, restart DHCP service, check static mapping, turn on VM.
Let me know if that works…
American here. As we all know, America is the only important country in the world so there is little need for African content…
Hi Joe, although with a somewhat heavy heart as I think there are some Americans who would say that seriously. I would also love more South African content. It’s a beautiful country with an interesting if checkered story and I would love to visit it someday.
That said, there are two things you should keep in mind. First off, whatever instance you’re on has a large effect on what you will see on Lemmy, so if you want more African content you might see if there is an instance running in Africa or at least subscribe to communities on that instance. You don’t have to join that instance in order to see them, but you do have to go looking for them.
Second, Lemmy has been largely adopted by a westernized population mostly of American and Western Europe origin, mainly because it provides a fediverse system with an experience similar to Reddit. Thus, much of Lemmy’s traffic is current or ex-redditors, which are mostly from the aforementioned demographics.