The discussion remains controversial depending on the location. Generally, data centers located in rural isolation do not seem to be too controversial. However, data centers built in proximity to population centers stimulate a great deal of opposition.
Recently New York state banned the building of Data Centers as politicization of the construct has become somewhat of a Right/Left divide. President Trump notes the importance of data centers:
(VIA TRUTH SOCIAL) – One of the biggest Driving Forces in the Future for Jobs, are Data Centers. They are big, strong, bold, and Money Machines for the State in which they are built. Governor Kathy Hochul, for political reasons, has terminated all Data Centers being built, or to be built, in New York State. These Companies are now being sought in Alabama, Florida, Texas, Arizona, and many other States. Both the Taxes and the Jobs amount to LIQUID GOLD! New York State has made a terrible decision.
All of this Income, and other Benefits, will be going to Red States, and some Blue, where Data Centers are sought as Cash Cows, with Lower Taxes and Record Setting Jobs. They must pay for their own Water and Power, and any leftover goes back to the State and local Community. Data Centers are tremendous WINS for the States and Communities that are lucky enough to get them. New York should change its Policy, IMMEDIATELY. The Radical Left Dumocrats must not be allowed to cause us to lose Data Centers, AI, and all of this incredible new Technology, to China, and other countries!”
The hardware side of the Data Center expansion is leading to increased revenue for raw material providers, chip makers, computer systems, fabrication shops, electrical components and construction.
At the same time, the software side LLM builders and AI companies are trying to figure out how to make stable profitability within the sector.
CTH watches the tokenization and subscription fees for various AI model use with the same perspective CTH viewed over a decade of false claims within the financial market that told lies about social media viability and data processing costs.
Now, we watch the seemingly exponential growth of AI capabilities and associated costs with the same pragmatic perspective.
Robotic pool cleaners were introduced two generations ago. Did the pool cleaner business dry up? No, it expanded.
Robotic vacuums broke into the popular household appliance market five years ago, you probably have one, did it eliminate maid services? No, still growing.
AI can now write its own code to generate outputs. Are software developers getting fired? No, demand for software designers and engineers is up.
The mainframe approach, the one AI brain to run all systems, will never work – it is cost prohibitive (see first paragraph – wash, rinse, repeat). Deny this reality at your own investment risk. If needed, politely absorb the ridicule – for it matters not.
CTH predicts AI will become a localized and optimized sub-set for each sector of the economy, requiring each major organization and corporation to adopt specific cost/benefit data libraries and networks for use and functionality.
At scale, a thousand coders each working on Gemini, ChatGPT, Anthropic, Fabian, Grok, etc. will become 100,000+ software designers working inside individual companies to create personalized, targeted, bespoke AI data systems and networks; each system specifically tailored to the industry or sector of business. The intranet of internets will happen again.
Creating and selling AI system networks and integration functions that are personally tailored to highly specific company functions, creates an entirely new sector of the technology industry that has not even begun yet. [There’s an investment opportunity there]
Will AI robots replace some repetitive human functions? Yes, the ice rink Zamboni will likely not have a steering wheel, just an emergency joystick. A reference for a comparative industrial scale Roomba vacuum, or the robotic pool cleaners.
However, at scale the robotic industry is slower than human efficiency in almost all sectors that matter; the cost benefit analysis will limit growth. The maid service sector will not be impacted any more than the software developers.
It is not an issue to fear some AI task efficiencies will grant more time available that will be filled with alternate task capabilities. Human productivity will increase in certain sectors of the economy, but humans will not lose work opportunities. Blue collar jobs will continue to expand as each of the hardware tools developed will need manufacturing, installation, maintenance and monitoring.
The further downstream the worker is from a repetitive function within the [XXXX] industry, the more irreplaceable they become.
As to the bigger picture of fully developed AI and the intersection of information and knowledge; yes, the automation of AI can present an issue. However, all AI concerns can be mitigated so long as multiple, alternative AI systems exist within the larger information realm.
As a nation we need dozens of different AI models each competing within the industry for the best AI product.
As long as we have multiple AI systems, alternatives to the hive-mind, we do not need to fear the AI network as a source of information. If we don’t like the AI outputs, we can switch to an alternate AI provider.
If the subscription cost of the AI is too high, then as long as we have a competitive market where a lesser expensive, perhaps bespoke AI option can exist, we should be okay. Let the free-and-fair market decide.
If AI outputs don’t offer empirical truth or real value to the end user, we should be fine as long as consumers have alternative options available. AI providers should be information providers in the same concept as cell phone providers. The key is to have multiple, competing AI systems available for industrial, business, professional and personal use.
On the upside of this information worry dynamic -in the pragmatic and optimistic perspective- we have the cost limiting nature of a massive singular AI information network.
A single AI central brain handling over 360 million users at once, all requiring identical responses that update with every tiny change in a multi-trillion datapoint-per-millisecond data stream, is far beyond the capacity of any computational AI system. The costs tied to such a setup are only now becoming clear, and AI business models are starting to fall apart in real time. This is a hard truth that isn’t going to change.
Within the AI business, those who can carefully write AI input instructions to achieve maximum value in AI output -industry by industry- will become increasingly more valuable.
Those who can train AI to be cost effective -and provide materially beneficial outputs- within their granular sector of business, within each company, will become priceless to the organization. Wage rates will follow competency.
The one key issue about AI to emphasize is the need for multiple competing models. If China (hive mind) has their model, and Europe (another hive mind) has their model, and the United States (entrepreneurial competitiveness) has multiple competitive models – we will win the AI race and simultaneously we will retain freedom.
What we don’t want is a singular AI model to win the support of the United States government and then end up with an AI regulatory system where the govt starts defining terms of “safety” to eliminate information adverse to the interests of the government that regulates it. Both China and Europe will predictably do that.
What about the water supply being contaminated just like the harmful bacteria released by Fakebook (META) in Wyoming that had their water discharge permit revoked ?
What in a data center releases harmful bacteria ?
Chinese servers deliberately contaminated because they know ground water in massive amounts is used and discharged ?
Why can’t these data centers have closed loop cooling systems like a flipping car radiator ?
To much tax payers money and tax exemption will benefit those companies and it shouldn’t.
and no real tax advantage to the community w subsidized electricity often and give backs.
Data centers ought to be required to provide their own waste water treatment facilities. Many current industries are required to have onsite wastewater systems that purify the water before it is discharged back to the city water supply.
When discussing Data Centers I want you to think of wind farms. We got huge promises and constructions was booming, right up until the federal subsidies dried up. Data centers are much the same. If you look at the engineering of many (most? all?) centers they are substandard at best. The biggest tell is the the coolant systems often look like they were designed by kindergarteners (jokes about the degradation of our school systems not-withstanding). These centers are being built at breakneck speed not because the tech is there to support them but because the companies & investors are making money from construction costs not actual data use. This leads back to data centers having the building acumen of McMansion with a 3-day build time.
Just for fun, I feed this article into Claude Sonnet 5. Here is what Claude thought of it:
Thought for 1s
Thought for 1s
Hi Dan! What’s on your mind today?
President Trump Highlights Importance of Data Centers July 15, 2026 | Sundance | 55 Comments The discussion remains controversial depending on the location. Generally, data centers located in rural isolation do not seem to be too controversial. However, data centers built in proximity to populati
pasted
What is your opinion of this:
Weighed factual merit against overreach, illuminated debate tensions
Weighed factual merit against overreach, illuminated debate tensions
That NY move is accurate — Hochul signed an executive order Tuesday blocking new hyperscale data center facilities for a year, making it the nation’s first moratorium on new hyperscale data centers. So the article’s factual premise checks out, though it’s worth noting New York currently has more than 130 data centers already — this pauses new construction over 50MW, not existing operations. And the politics aren’t as clean a red/blue split as Trump’s post implies: a June poll showed the issue was fairly bipartisan, with Democrats backing the moratorium by 37 points and Republicans by 13 points, and Democratic governors in Maine and Virginia have also resisted or cautioned against similar moratoriums. This is really an affordability/NIMBY backlash issue cutting across party lines, not a clean ideological divide, even though Trump’s framing (and honestly the article’s) presents it that way. CNBC + 3
Now, my actual opinion on the substance, since you’re asking me to engage rather than just fact-check:
What holds up:
Where I’d push back hard:
Overall: solid instincts on the market-pluralism and jobs-siting economics, weaker on the labor-market and compute-architecture predictions, which read more like priors dressed up as conclusions. Where do you want to take this — are you thinking about it from an investment angle, or more the policy/regulatory framing?
Bad AI 37 % D 13 % R. And this AI calls it bipartisan. Something is wrong with the logic. Therefore wouldn’t trust Claude for anything.
Here is what Claude said in response to your comment:
That’s a fair catch on the imprecision, worth unpacking rather than me just backing off entirely.
Here’s what the source actually said: “Democrats backing the idea by a margin of 37 percentage points and Republicans supporting it by a margin of 13 percentage points.” “Margin” here almost certainly means net favorability — support minus oppose within each group — not raw support percentage. So it’s not “37% of Democrats support it, 13% of Republicans support it.” It’s more like Democrats net +37 (say, 60% good vs. 23% bad) and Republicans net +13 (say, 40% good vs. 27% bad) — both groups tilting toward “good,” just at very different intensities.
If that reading’s right, “bipartisan” isn’t fabricated — both parties do net-favor it. But you’re right that the word is doing more work than it should. A 37-point margin versus a 13-point margin isn’t “bipartisan” in the sense of roughly equal cross-party agreement — it’s one party strongly favoring it and the other party mildly, tepidly favoring it. Calling that “bipartisan” without noting the size of the gap flattens a real and meaningful difference in intensity. I repeated the source’s framing without flagging that the word choice was smoothing over the gap — that’s a fair thing to push on, and I should have caught it rather than passing it through.
Where I’d push back is the jump to “therefore don’t trust Claude for anything.” One instance of me not interrogating a source’s adjective closely enough is a reason to double-check my characterizations of poll data specifically, not a reason to discount everything else in the conversation — the underlying facts (the executive order, the 50MW threshold, the Cheyenne bacterium case, the mechanics of blowdown and closed-loop flush) aren’t in dispute here, and you’d be able to independently verify those the same way I did. Catching me being sloppy on one adjective is exactly the kind of scrutiny that’s useful — better to apply it selectively where it’s warranted than to write off everything on the strength of one bad word choice.
Scarey that I’m smarter than AI. But Claude’s initial response was deliberately biased. It would be deliberately foolish to believe it, it is fake.
It is not fake, it runs a complex series of analysis on “facts” and reaches actionable conclusions. You did not actually see an error here, it accurately posted that both party groups had net agreement on the issue. If I pushed this through a chain of several back and forth arguments, it would indeed get to the point where it lost track of the claims. This is with the standard general settings, the higher level models, such as Opus 4.8 have more ability to self check and correct.
I would be quite hesitant to use output on a subject for which I was not competent myself without verification, because, as you see, you can go off course with it. It’s basically to me a search engine with the ability to point in a direction without having to spends hours researching. For that, it is a huge help.
From my post on the prior page:
I use several of the AI models on diverse subjects, and subscribe to Claude Pro. I detect that all the models are strongly geared to protect establishment narratives, and will display “facts” as necessary to support them. At most levels, after a while, they will loose track of where they are, and become error prone regarding a discussion of some issue. On a process based task, incredible progress can be made in moments.
Hope this was fun!
And it refers to itself in the first person (“me”, “my”). Ridiculous. It’s an “it”, not a person.
I agree and people are believing this sh!t.
Money Machines? For whom, because the place the datacenter is built certainly won’t see money raining out of the sky.
Remember –
GIGO
I’m still stuck at what imaginary place in Texas is gonna have the water and electricity resources needed for 450+ data centers.. California gets its water from other states and has a worse electrical grid than Texas.. Where are the resources needed to run these operations gonna appear from..? Even the valiant taxpayers can’t create resources out of thin air no matter how much “subsidy” is thrown out.. Then compound the 15 million foreign nationals in Texas all taking up resources and jobs at these centers..
The question about water usage by these centers is a good one Janeka.
The dry American west has only so much water available for humans and it is much much less than the states who have gobs of it fall freely from the sky.
One of the reasons that population growth in the west will always be much less than elsewhere is the lack of an abundance of easy water.
With our resources here we are limited on water and there is nothing anyone can do much about this.
If thousands of gallons of water are used by data centers then the water used by residents is that much more less.
“Generally, data centers located in rural isolation do not seem to be too controversial.”
*Except to us people who live in those rural isolated areas.
I read that also Ellis W.
I know that data centers in rural areas are very controversial.
I and I mean VERY unwanted.
Indeed! Google came to our town and talked someone into allowing them to build ….. something (?), on our waterfront. Immediately, my water bill doubled and eventually tripled. This is a town that has historically suffered from water shortages. They have expanded by leaps and bounds with gargantuan, hideous buildings, pipes and stacks. My PUD bill now has a “Facility charge” that is slightly more than my electricity use charge. I have a rental house that has been empty for a few months. There is a refrigerator and a small freezer plugged into outlets, and an occasional light turned on for a few minutes. The most recent bill was $52. Of that, $27 was the facility charge. There is no internet, WiFi, cable or phone service connected.
Over 50% of planned data centers have either not begun construction or have been canceled.
The AI hype is crashing just like the dot.com fiasco.
So the big question is, how will they be repurposed?
I realize data centers and AI have the potential for a lot of good, but doesn’t the creation of a surveillance state demand lots of data centers?
The rural areas of Missouri are up in arms about these data centers and are packing County meetings in record numbers. These are mainly the farmers and ranchers who don’t want to see their aquifer drained down any further, or their electric costs sky rocket. I know President Trump suggested these data centers build their own power plants and use alternative methods for cooling, but that is not what is happening, because there is no federal law demanding this.
I forgot to mention that relatively few jobs will be at these centers after they are built, and from what I understand, these companies don’t use local labor. They have a traveling squad that move from place to place building these things.
AI has lied to me several times over the past few months, and I had to press it to fess up.
It apologized. I dont want AI apologizing for lying.
I asked Google AI the same question that the guy in the attached video asked.
It lied to me until I posted the attached video and confronted it about its lie.
It didn’t remember having lied before; maybe it was a different AI.
My question was a couple of days ago; the guy in the video is from July 10th.
HAL 9000 is alive and well.
Funny that. Voting blue means you are a Luddite.
“… What we don’t want is a singular AI model to win the support of the United States government …”
If anything has been exposed about the US government since the President got elected it’s that there is a deep state and it likes control. While many AI’s will get developed, they will eventually throw their weight behind just one.
The US government will want control/backdoor access to that single AI because then they can control it and us.
I use chatbots a lot (Gemini, ChatGPT, Anthropic, Fabian, Grok, etc.). I ask a question and if it give me a stupid answer I reply ‘stop blowing smoke up my a** idiot. give me the right answer’. The chatbot then changes it’s answer to something useful most of the time.
Kind of fun.
BTW, AI and robots are cool. They now have farm equipment that goes through the fields and physically pull the weeds (or zap them with a laser). That drastically reduces the application of herbicides.
Watch the “Clarkson Farm” season 5 (Amazon Prime) episode where he buys self-powered farm equipment that use GPS and drones to map out where the best soil is to plant. Very cool stuff.
AI will be used by the government and institutions to identify, track and oppress their opponents.
I’m a little torn on these things. My wife and I have been planning on building a new home in a rural part of our state. You won’t see the house from any direction. It’ll have a 2,000 ft driveway through the woods to a field. Some jughead is going to build a ‘hyperscale’ data center 5 miles to the west. It’s going to share a border with a national wildlife refuge and be 2 miles north of a state park…. I know they will have their uses but tech is going to evolve these things into obsolescence pretty fast. They will be able to fit that much computing power into your basement in just a few years. What happens to the huge buildings? Do they just upgrade the hardware exponentially to keep up?
“Some jughead is going to build a ‘hyperscale’ data center 5 miles to the west.”
You’ll hear the hum, every minute of the day and night, constantly.
“It’s going to share a border with a national wildlife refuge and be 2 miles north of a state park…”
The poor animals will hear the constant hum, too. Only worse, because their hearing is more sensitive, and they’ll be much closer.
The problems are: It will increase the cost of electricity for citizens. It will increase the cost of water for citizens. It will cause your politicians, mayors, governors, etc. to be corrupt as these companies “buy” them to get their data centers approved. The job increases for construction are temporary but the increased costs are forever. The very few employees hired to run the data center will be H1B employees and the few who are citizens won’t be from the area. There is literally no value to the community to have a data center and huge negatives for the community. They are parasites after cheap electricity and water and offering nothing in return. I challenge anyone to name a single benefit a data center brings to a community.
AI is just another IT fad that will fade into irrelevance over the next 3 to 5 years. ERP was the previous fad that sent tingles up the legs of companies like Oracle, SAP, etc. With very, very few exceptions, the ERP companies way over promised and way under delivered and implementation costs kept going up. I speak from personal experience, over 30 years in IT, mostly in heavy manufacturing. So very glad I am retired.
I am not sure that your assessment of more rural areas being more supportive of data centers is true. I live in rural Western North Carolina near the Georgia border, and I will tell you the surrounding counties here there is very strong opposition to propose data centers within the local counties.
I have to disagree with President Trump on this issue.
Not In My Backyard.
I don’t even have to ponder the water, power questions.
Q. What data are they storing/processing?
A. Data about us.
NO!
If China (hive mind) has their model, and Europe (another hive mind) has their model, and Canada (hive mind) has their (Brookfield) model