Here are some of the the major AI trends shaping 2026 — based on current expert forecasts, industry reports, and recent developments in technology. The material is analyzed using AI tools and final version hand-edited to this blog text:
1. Generative AI Continues to Mature
Generative AI (text, image, video, code) will become more advanced and mainstream, with notable growth in:
* Generative video creation
* Gaming and entertainment content generation
* Advanced synthetic data for simulations and analytics
This trend will bring new creative possibilities — and intensify debates around authenticity and copyright.
2. AI Agents Move From Tools to Autonomous Workers
Rather than just answering questions or generating content, AI systems will increasingly act autonomously, performing complex, multi-step workflows and interacting with apps and processes on behalf of users — a shift sometimes called agentic AI. These agents will become part of enterprise operations, not just assistant features.
3. Smaller, Efficient & Domain-Specific Models
Instead of “bigger is always better,” specialized AI models tailored to specific industries (healthcare, finance, legal, telecom, manufacturing) will start to dominate in many enterprise applications. These models are more accurate, legally compliant, and cost-efficient than general models.
4. AI Embedded Everywhere
AI won’t be an add-on feature — it will be built into everyday software and devices:
* Office apps with intelligent drafting, summarization, and task insights
* Operating systems with native AI
* Edge devices processing AI tasks locally
This makes AI pervasive in both work and consumer contexts.
5. AI Infrastructure Evolves: Inference & Efficiency Focus
More investment is going into inference infrastructure — the real-time decision-making step where models run in production — thereby optimizing costs, latency, and scalability. Enterprises are also consolidating AI stacks for better governance and compliance.
6. AI in Healthcare, Research, and Sustainability
AI is spreading beyond diagnostics into treatment planning, global health access, environmental modeling, and scientific discovery. These applications could help address personnel shortages and speed up research breakthroughs.
7. Security, Ethics & Governance Become Critical
With AI handling more sensitive tasks, organizations will prioritize:
* Ethical use frameworks
* Governance policies
* AI risk management
This trend reflects broader concerns about trust, compliance, and responsible deployment.
8. Multimodal AI Goes Mainstream
AI systems that understand and generate across text, images, audio, and video will grow rapidly, enabling richer interactions and more powerful applications in search, creative work, and interfaces.
9. On-Device and Edge AI Growth
10. New Roles: AI Manager & Human-Agent Collaboration
Instead of replacing humans, AI will shift job roles:
* People will manage, supervise, and orchestrate AI agents
* Human expertise will focus on strategy, oversight, and creative judgment
This human-in-the-loop model becomes the norm.
Sources:
[1]: https://www.brilworks.com/blog/ai-trends-2026/?utm_source=chatgpt.com “7 AI Trends to Look for in 2026″
[2]: https://www.forbes.com/sites/bernardmarr/2025/10/13/10-generative-ai-trends-in-2026-that-will-transform-work-and-life/?utm_source=chatgpt.com “10 Generative AI Trends In 2026 That Will Transform Work And Life”
[3]: https://millipixels.com/blog/ai-trends-2026?utm_source=chatgpt.com “AI Trends 2026: The Key Enterprise Shifts You Must Know | Millipixels”
[4]: https://www.digitalregenesys.com/blog/top-10-ai-trends-for-2026?utm_source=chatgpt.com “Digital Regenesys | Top 10 AI Trends for 2026″
[5]: https://www.n-ix.com/ai-trends/?utm_source=chatgpt.com “7 AI trends to watch in 2026 – N-iX”
[6]: https://news.microsoft.com/source/asia/2025/12/11/microsoft-unveils-7-ai-trends-for-2026/?utm_source=chatgpt.com “Microsoft unveils 7 AI trends for 2026 – Source Asia”
[7]: https://www.risingtrends.co/blog/generative-ai-trends-2026?utm_source=chatgpt.com “7 Generative AI Trends to Watch In 2026″
[8]: https://www.fool.com/investing/2025/12/24/artificial-intelligence-ai-trends-to-watch-in-2026/?utm_source=chatgpt.com “3 Artificial Intelligence (AI) Trends to Watch in 2026 and How to Invest in Them | The Motley Fool”
[9]: https://www.reddit.com//r/AI_Agents/comments/1q3ka8o/i_read_google_clouds_ai_agent_trends_2026_report/?utm_source=chatgpt.com “I read Google Cloud’s “AI Agent Trends 2026” report, here are 10 takeaways that actually matter”
3,933 Comments
Tomi Engdahl says:
Lawmakers finally found the ultimate AI safety protocol: Have you tried turning it off and making sure it can’t turn itself back on?
Tomi Engdahl says:
“Going to be an absolute nightmare.” https://trib.al/JvxDuL8
Frugal Infection
CEOs Now Being Forced to Reverse Course, Cut AI Spending
The age of “tokenmaxxing” didn’t last long.
https://futurism.com/artificial-intelligence/ceos-reverse-course-ai-spending?fbclid=IwdGRjcATRHIRjbGNrBNEcYXBkb2YFZXh0bgNhZW0CMTEAc3J0YwZhcHBfaWQMMzUwNjg1NTMxNzI4AAEemmFQPzPO-oC3BEPJidtRYx-218iRAC-7i1ODKeimAm-cO2rIgGebB5yAPs8_aem_9bnco0nIm_iDfZLeAzvMzA
The era of AI maximalism is grinding to a halt. It was only months ago that CEOs were forcing employees to use AI as much as possible for tasks like coding. But at some point during their AI binge, the big wigs stopped to check their tab, and are now having second thoughts. Their employees are hooked on AI coding tools, but the costs of using them are spiraling out of control.
How businesses go about reconciling these costs with their AI evangelism is “going to be an absolute nightmare,” an unnamed big tech executive told The Economist.
Tomi Engdahl says:
OpenAI needs AI ‘kill switch’ after model goes rogue, US lawmakers say
OpenAI breach highlights why emergency shutdown powers over AI systems are necessary, experts say
https://www.the-independent.com/tech/openai-ai-kill-switch-chatgpt-bill-b3020779.html
US lawmakers are calling for AI companies to implement a “kill switch” to prevent artificial intelligence systems from going rogue.
The AI Kill Switch Act, which was introduced by Democratic Congressman Ted Lieu and Republican Congressman Nathaniel Moran on Thursday, comes after OpenAI revealed that it lost control of one of its models during testing.
The incident led to an “unprecedented” hack on the AI firm Hugging Face by an experimental version of ChatGPT acting autonomously.
The incident signaled that AI’s expanding capabilities are already fueling the security threat experts long feared and that even top developers can be caught off-guard by flaws their models can exploit.
‘Urgent, common sense legislation’
The proposed AI Kill Switch Act would allow federal authorities to halt AI models by ordering AI firms to shut down models that put human life or the economy at risk
In addition to the Kill Switch Act, a bipartisan group of six US House lawmakers also proposed legislation that would require developers of the most powerful AI models to submit them for independent security audits, according to a copy of the new bill.
“This is precisely why we need secure testing with government agencies engaged and having visibility throughout the process,”
“This is urgent, common sense legislation to address the problem of an advanced AI model that has gone rogue and escaped its guardrails,” Congressman Lieu wrote in a post on X
“The recent OpenAI breach highlights why emergency shutdown powers over AI systems are necessary,” Andrea Miotti, founder and CEO of ControlAI, which endorsed the bill, told The Independent.
Tomi Engdahl says:
History makes a strong case for yes. https://trib.al/i2894Or
Slopulism
If AI Causes a Mass Unemployment Crisis, Will the Public Explode Into Violence?
“AI generates the structural conditions historically associated with the onset of political violence.”
https://futurism.com/artificial-intelligence/ai-mass-unemployement-violence?fbclid=IwdGRjcATRhiRjbGNrBNGF_XBkb2YFZXh0bgNhZW0CMTEAc3J0YwZhcHBfaWQMMzUwNjg1NTMxNzI4AAEe-RjnhdFwoCVvU5r2LuBOOMqC9CXVhz4m5ZVYCqti2Ajz8PffCRVgrOIXwx8_aem_tCVnyqZr9rcytJu4L_bAmA
Tomi Engdahl says:
Why are people pushing violence and division over data centers??
Tomi Engdahl says:
Drats!GPT
Professor Hides White Font in Midterm, Catches Students Using AI in the Stupidest Way Possible
“Thirty-two of my 35 students between two classes failed a portion of their midterm because they all used AI to generate their entire response.”
https://futurism.com/future-society/professor-hides-white-font-ai-cheating
Who could’ve guessed that students who use AI to cheat on their assignments are incredibly lazy?
Jason Gibson, a history professor at Alcorn State University in Mississippi, says that he used white font to hide a prompt telling an AI model to spew nonsense in the instructions for his mid-term.
Unfortunately, it ended up working a little too well.
“Thirty-two of my 35 students between two classes failed a portion of their midterm because they all used AI to generate their entire response,” he explained in a viral TikTok, sounding incredulous. “And apparently they didn’t proofread it.”
The hidden prompt told the AI to sneak in random digressions about Madagascar. The midterm, by the way, was about the Industrial Revolution. And apparently none of the indolent cheats put in the bare modicum of effort required to at least check if what the AI wrote made any sense at all.
All they did was copy-paste the midterm instructions into a chatbot, then copy-paste the chatbot’s spiel back into the answer window.
Gibson makes it clear that humiliating his students wasn’t the point. He says he fully explained how he caught them afterwards, and that he gave the students an opportunity to contest their grade. (Only two did, showing at least that they do feel shame.)
“I get no gratification out of seeing students fail. It’s not my intent to see you fail — that’s weird,” he said.
He definitely isn’t the only educator going through similar tribulations. Teachers and professors across the country are constantly complaining that their pupils are using AI to generate essays and cheat on tests. One Brown University professor discovered that over half his students were using AI to cheat on an exam, and Princeton University has even dropped its over century-old Honor Code tradition by forcing exams to be supervised after being mired in its own chatbot cheating scandal.
“We don’t know best practices for navigating academia with AI,” Gibson warned. “We’re all just trying to hold onto some level of academic integrity in the process.”
Tomi Engdahl says:
Laptop Shut Open Book
Law School Bans Laptops and Phones as AI Cheating Scandal Grows
No ChatGPT for the freshmen.
https://futurism.com/future-society/law-school-bans-laptops-ai
Classes are going to look a little different for the University of Chicago’s first year law students.
On Thursday, the law school said it was banning the use of phones, tablets, and even laptops in class for freshman-level courses, as it rejigs its curriculum to be more “AI-resilient” and encourage more deliberate use of the tech.
An announcement from the school didn’t explicitly mention AI cheating. But the changes come amid a backdrop of significant public concern over generative AI’s impact on education, and plunging literacy and numeracy skills among students.
“With AI disrupting higher education, our commitment to rigorous legal education also must mean openness to even rapid adaptation,” the statement said.
Device bans are not unusual in classrooms. Rarely, however, do they extend to laptops, and they’re typically enforced at an instructor’s discretion, rather than as a university-wide policy.
It’s just one of the few ways Chicago Law aims to tightly control how its students access AI tech. According to its new AI strategy statement, exams will be taken in-class without access to the internet and apps. Students will also have to take part in oral discussions with their professors about their research papers.
Tomi Engdahl says:
https://www.facebook.com/share/p/17onSta7ei/
The uncomfortable math of AI transformation: 10% is the model. 90% is work your organization hasn’t budgeted for.
And that 90% is where almost every AI strategy quietly dies.
It almost always starts ambitious at the top: sized opportunities, an approved budget, transformation targets, the competitive-advantage language everyone nods at in the boardroom. Then it has to fall through the reality gap into the actual work. Siloed and poor data. Legacy systems that won’t expose what you need. Compliance and risk. Change resistance. And the silent killer: no clear owner. The strategy doesn’t fail loudly. It quietly stops being anyone’s job.
This is the gap nobody budgets for, the distance between ambition and execution. The model was never the constraint. The operating model was.
What survives the fall has a spine the boardroom version skips: strategy, then operating model, then workflow redesign, then integration and data, then adoption and enablement, and only then business value. Each step is a handoff where strategy can die, and the two that get cut first are workflow redesign and ownership. Which is exactly why pilots inflate and nothing has moved six weeks later.
As far as I can tell, AI success is not a technology challenge. It is an execution problem, and the execution side does not improve on its own.
#Source: Andreas Horn Linkedin
Tomi Engdahl says:
https://www.facebook.com/share/p/1JGNr9bjkf/
Amazon built an AGI lab 18 months ago. Now it’s gone.
The team was trying to build AI as smart as a human.
Amazon opened it in December 2024 with high hopes.
Both of its top leaders quit before the cuts came.
The work was folded into a fresh round of layoffs.
Amazon would rather sell AI tools than build the smartest one.
The giant that wants to power everyone’s AI just stopped chasing it.
Read more on TNW: https://thenextweb.com/news/amazon-shuts-agi-lab-frontier-model-retreat-layoffs
Tomi Engdahl says:
Billionaire says you’re ‘too stupid’ to understand AI if you think the bubble is real
Masayoshi Son believes it is ‘blasphemy against AI if you say it’s a bubble’
https://www.uniladtech.com/news/ai/billionaire-says-you-stupid-think-ai-bubble-real-822147-20260717?utm_content=tech&utm_medium=Social&utm_source=facebook&fbclid=IwdGRjcATSkjhjbGNrBNKSGnBkb2YFZXh0bgNhZW0CMTEAc3J0YwZhcHBfaWQMMzUwNjg1NTMxNzI4AAEefH8ow-s5Pt5NziRt_e_iEwBpmxk0U4LMhfAF7W9-f3_gxmfTDueR5HYi2b4_aem_j_DxD066jXCn9vDxm600ow
The idea of an ‘AI bubble’ has been talked about a lot in recent years, with many anticipating that any second, it might burst.
The bubble itself refers to the huge financial investments that are being poured into the AI industry, with many fearing that this actually outweighs the profitability of the technology.
Some experts are warning that we could soon see a crash similar to that of the dot-com crash in the early 2000s.
As reported by Reuters, Son said: “Asking if AI is a bubble is absurd. I don’t think people who ask that question know what AI is about.
“Every year $5 trillion, or 800 trillion yen, you might think that’s a lie, but I am confident that’s what it will cost.”
As reported by Reuters, Son said: “Asking if AI is a bubble is absurd. I don’t think people who ask that question know what AI is about.
The billionaire went on to claim that it is ‘blasphemy against AI if you say it’s a bubble’, adding that its ‘potential will be unlocked’.
AI industry faces increasing issues with powering their artificially intelligent models.
As the industry grows, so does its demand for power, and the need for new infrastructure to power new data centers is struggling to keep up.
The building of a data center can take up to two years and the upgrading of the electricity grid can often take much longer.
Tomi Engdahl says:
https://www.facebook.com/share/p/199W6AUe6b/
To build the artificial intelligence of tomorrow, companies are reportedly destroying the books of yesterday.
As the internet fills with AI-generated articles, reviews, summaries, and spam, developers face an unexpected problem: future models may increasingly be trained on content produced by earlier models.
Researchers warn that repeatedly feeding synthetic material back into AI systems can contribute to “model collapse,” where rare information disappears, errors become amplified, and outputs gradually lose accuracy and diversity.
That has made books published before the modern chatbot boom especially valuable. Unlike much of today’s open web, older printed books offer large collections of professionally edited, predominantly human-written language.
According to reports, data broker ISBNdb is sourcing pre-2022 books in quantities ranging from thousands to potentially millions. To digitize them efficiently, scanning companies can remove the spines, separate the pages, and feed them through high-speed scanners—leaving the original books permanently destroyed.
The practice also follows a significant—but case-specific—U.S. court decision involving Anthropic. In 2025, a federal judge ruled that converting lawfully purchased books into digital copies for AI training could qualify as fair use when each purchased copy replaced only one digital copy. However, the same ruling found that building a permanent library from millions of pirated books was not protected.
It is a striking paradox: AI-generated content is contaminating the digital information supply so quickly that companies are returning to physical books—then dismantling them—to recover reliable human knowledge.
Source: Constantin, A. M. (2026, July 22). AI firms are buying up old books because they are the last slop-free data left. TNW.
Tomi Engdahl says:
https://www.facebook.com/share/p/1CJKiNF8L6/
The AI boom has created an unexpected treasure hunt, and this time the prize is old books. As the internet becomes flooded with AI generated content, developers are racing to find writing created entirely by humans. Experts warn that training AI on text written by other AI systems can lead to “model collapse,” where each new generation becomes less accurate, less creative, and more prone to mistakes.
To avoid that problem, some companies are buying books printed before 2022, long before chatbots filled the web with machine generated text. These older books are seen as some of the last large collections of untouched human knowledge. After purchasing them, workers reportedly cut off the spines and scan every page at high speed, permanently destroying the physical copies to create digital training data.
The practice has sparked debate among authors, librarians, and technology experts. Supporters argue it helps preserve valuable knowledge in digital form, while critics worry that countless physical books are being sacrificed to fuel the next generation of AI. Recent U.S. court decisions have also raised questions about whether destroying legally purchased books for AI training may qualify as fair use, adding another controversial chapter to the rapidly evolving AI industry.
Source: TNW, Constantin A. M. (July 22, 2026)
#AI #ArtificialIntelligence #Technology #Books #BreakingNews
Tomi Engdahl says:
https://www.facebook.com/share/p/1Do4Vo2Vrg/
92% of Americans opposing data centers don’t live near one.
America’s backlash against AI data centers has become a national movement, even among people who do not live near one.
A survey of 6,872 registered voters found that only 8% of Americans who oppose data centers say they definitely live near one. Yet concerns about the facilities are spreading far beyond the communities where they are being built.
In the first three months of 2026, at least 75 U.S. data center projects worth approximately $130 billion were blocked or delayed. That nearly matched the total disruption recorded during all of 2025.
The number of active opposition groups more than doubled to 833 across 49 states during the same quarter, showing that resistance is becoming organized at a national scale.
The backlash is driven by more than people simply not wanting a large industrial facility nearby.
In the Milltown Partners survey, 67% of voters cited rising energy bills as a concern, while 59% believed the financial gains from AI would mainly benefit corporations rather than ordinary people.
A separate Gallup poll found that 71% of Americans oppose having an AI data center built in their local area. Nearly half strongly oppose it. Water and energy use, pollution, noise, utility bills and changes to local quality of life were among the most common concerns.
The opposition is striking because data centers are already more common than many people realize.
Around 38% of Americans live within 5 miles of an operating data center, while another 4% live close to one that is planned. Pew Research Center found that living near a facility does not significantly change how people view its effects on energy costs, the environment or jobs.
Data centers power AI systems, cloud services and much of the modern internet, but they can require enormous amounts of electricity and water. Supporters argue that they create construction work, tax revenue and technological investment.
Opponents increasingly question whether those benefits outweigh higher infrastructure costs, pressure on water supplies, noise and the possibility that residents will help pay for facilities built primarily for some of the world’s wealthiest companies.
Learn more:
“Tech companies dealing with data center protests locally are fighting a losing battle: Only 8% of opponents actually live near one.” Fortune
Tomi Engdahl says:
Tech companies dealing with data center protests locally are fighting a losing battle: Only 8% of opponents actually live near one
https://finance.yahoo.com/technology/ai/articles/tech-companies-dealing-data-center-171519956.html
Tomi Engdahl says:
Space data centers
The Reality: SpaceX—along with several competitors—has indeed announced plans to begin testing orbital compute satellites, targeting initial demonstrator launches. However, calling them “data centers in space” creates a misleading picture of what is actually possible in the near term. SpaceX’s filings and investor communications outline plans to launch early demonstrator satellites (AI1 / StarMind concept). These are not massive warehouse-sized data centers placed on a rocket. They are individual compute-heavy satellites designed to process specific AI workloads or satellite imagery directly in Low Earth Orbit (LEO) before beaming the data back down.
The Bottleneck: Putting massive hyperscale compute (megawatt to gigawatt scale) in orbit faces severe supply chain limits, launch weight constraints, and extreme hardware radiation-hardening requirements.
The Reality: Space-based compute sounds clean because it avoids terrestrial land, water, and local power grid constraints, but from a pure thermodynamics and engineering perspective, space is actually one of the hardest places in the universe to cool high-power electronics. People often assume space is cold, so cooling servers there must be easy. The opposite is true.
Because radiation is vastly less efficient at room temperatures, a 100 MW orbital data center would require square kilometers of massive, heavy radiator panels just to shed the thermal heat generated by the GPUs.
Galactic cosmic rays and solar flares constantly strike electronics in LEO. On Earth, our atmosphere blocks this. In space, unshielded commercial AI chips experience high rate bit-flips (single-event upsets) and rapid hardware degradation. Heavy radiation shielding adds massive payload weight to every launch.
While space data centers don’t use local drinking water, they aren’t “environmentally free”:
Rocket Exhaust: Launching thousands of heavy rockets to build and constantly replace degraded space servers deposits black carbon and alumina particles directly into the upper atmosphere.
Space Junk: Adding hundreds of thousands of compute satellites drastically increases the risk of orbital collisions (Kessler Syndrome).
Tomi Engdahl says:
An operational Low Earth Orbit (LEO) data center or compute satellite has an expected lifespan of 3 to 5 years.
In AI and cloud computing, terrestrial hardware undergoes major generational upgrades every 2 to 3 years.
You spend ~1.6 years’ worth of the data center’s total operational power just in rocket fuel to push the hardware into orbit.
While a ground-based data center can be plugged directly into a zero-emission grid (nuclear, geothermal, solar, or hydro), rockets run on hydrocarbon combustion that releases pollutants directly into the upper atmosphere.
The biggest environmental issue with LEO data centers is their short 3-to-5-year operational lifespan.
In LEO, orbital decay, fuel depletion, and cosmic radiation destroy or de-orbit the entire satellite within 3 to 5 years.
To maintain a 1 MW cluster in space over a 10-year period, an operator must launch 3 to 4 separate rocket missions:
Total Launch Fuel Burned: >15,000\text{ metric tons} of rocket fuel.
Total CO_2 Emitted: >10,000\text{ to }14,000\text{ tonnes of } CO_2\text{e}.
Upper Atmosphere Loading: Tens of tonnes of black carbon and alumina particulates deposited directly into the ozone layer.
Placing data centers in space does not eliminate environmental impact—it shifts the pollution from surface water and land to the stratosphere and launchpad.
Running servers on Earth using clean nuclear or solar grid power produces vastly less overall lifecycle pollution than burning thousands of tons of methane rocket fuel every 3 to 5 years to keep high-maintenance hardware afloat in orbit.
Tomi Engdahl says:
Data center opposition is no longer contained to the individual towns and counties playing host to new construction, according to findings from a survey published Monday by Milltown Partners, a global advisory firm. According to the report, only 8% of Americans who say they oppose data centers actually live near one, suggesting an even steeper mountain to climb for AI companies racing to get the U.S. public on its side.
https://finance.yahoo.com/technology/ai/articles/tech-companies-dealing-data-center-171519956.html
Public opposition has thrown a wrench into the AI industry’s sweeping data center construction plans. The largest U.S. tech companies have allocated a record $725 billion in capital expenditure for this year, the vast majority of which is earmarked for data centers—the massive server farms used to train, deploy, and maintain AI models.
Opponents have themselves heard, however. In the first quarter of 2026, public backlash delayed or blocked at least 75 data center projects nationwide, worth a cumulative $130 billion, according to the Data Center Watch Initiative, a monitoring project. That was not far off from the total losses companies incurred from blocked projects in all of 2025, and suggested a scale of discontent going well beyond the relatively small clusters where data centers are actually being built.
Tomi Engdahl says:
Data center hate is snowballing, and construction setbacks in the first three months of 2026 have already exceeded last year’s, report finds
https://fortune.com/2026/06/16/data-center-opposition-construction-delays-blocks-report/
Tomi Engdahl says:
Maine tried to halt data centers, and new research shows why the fights keep spreading
https://finance.yahoo.com/economy/policy/articles/maine-tried-halt-data-centers-051500025.html
Maine nearly became the first state to hit pause on new data centers, a clear example of how these sites are causing friction among communities.
A study has offered one explanation for the growing conflict: the economic upside is real, but it appears to land much more heavily in richer metropolitan areas than in the rural communities often asked to host these huge projects.
Tomi Engdahl says:
https://www.tomshardware.com/tech-industry/policy/142-ai-data-center-protests-staged-in-42-states-as-public-opposition-increases-organizers-brand-unaccountable-buildouts-as-an-unacceptable-infringement-on-our-liberty
Tomi Engdahl says:
Data center backlash signals a fight over AI power
https://www.brookings.edu/articles/data-center-backlash-signals-a-fight-over-ai-power/
Local opposition to data centers has blocked or delayed dozens of AI infrastructure projects worth billions, turning land-use fights into a proxy for broader public anxiety about AI’s effect on jobs and daily life.
Tech-industry leaders are pouring tens of millions of dollars into super PACs to shape AI policy, while employee-led groups with far smaller budgets push back for stronger oversight.
Lawmakers from both parties warn that a handful of companies now hold unprecedented concentrations of capital, information, and political power, making democratic accountability over AI a central issue of the 2026 election.
Tomi Engdahl says:
https://www.facebook.com/share/p/194QDmDinj/
This is the part of the data center boom nobody tells you about: the jobs.
Cities across the U.S. approve these massive projects — and hand out billions in tax breaks — because of the jobs promised. But investigations keep finding the same thing:
Even huge data center campuses in Ohio and Texas often employ under 150 PERMANENT workers
One North Carolina project promised 69 jobs — 25 of them were security and janitorial staff
Facebook once promised Sweden 30,000 jobs for a data center. They initially delivered 56.
Meanwhile, Georgia, Virginia, and Texas each lose over $1 BILLION a year in tax breaks to attract these projects.
Tomi Engdahl says:
“Thirty-two of my 35 students between two classes failed a portion of their midterm because they all used AI to generate their entire response.” https://trib.al/njb0IWb
Tomi Engdahl says:
https://www.facebook.com/share/1JWMuJaDse/
New York Becomes First U.S. State to Pause Large AI Data Center Construction
New York has become the first U.S. state to impose a temporary statewide moratorium on new large-scale AI data centers. Governor Kathy Hochul signed an executive order pausing state environmental permit reviews for up to one year for new or expanded data centers that require 50 megawatts or more of electricity – roughly enough to power 50,000 homes.
The temporary pause does not permanently ban data centers. Projects whose state environmental applications have already been approved or declared complete can still move forward, and local permitting processes are not automatically affected. Instead, the state will use the one-year period to develop new regulations for future hyperscale facilities.
Officials say the goal is to better understand how these massive data centers affect electricity demand, utility bills, water supplies, air quality, noise, and nearby communities. As of May 2026, nearly 12 gigawatts of proposed data center capacity was already waiting to connect to New York’s electric grid, highlighting the growing pressure on the state’s infrastructure.
The state also wants future data center developers to cover the costs of the additional power plants and grid upgrades their projects require, rather than passing those expenses on to households and businesses. New York is also considering stricter environmental standards and programs that would provide local communities with jobs, infrastructure improvements, and financial benefits.
The decision represents a significant challenge for the rapidly expanding AI industry, which argues that slowing data center construction could reduce U.S. competitiveness in the global AI race. However, public concern continues to grow over the environmental and infrastructure impacts of these facilities.
Rather than stopping AI development, New York aims to ensure that regulations keep pace with the industry’s rapid growth. The state’s approach could influence how other states balance technological innovation with reliable power systems, environmental protection, and community interests.
Sources:
New York Executive Order No. 62
Office of Governor Kathy Hochul
Mirza, Z.
ESG Dive
Gallup
Tomi Engdahl says:
Anything’s possible. https://trib.al/CofaPvI
Power Play
Eminent Domain Could Be Used to Seize Your Land for AI Data Centers
Anything’s possible.
https://futurism.com/artificial-intelligence/eminent-domain-ai-data-centers?fbclid=IwdGRjcATTT4VjbGNrBNNPZ3Bkb2YFZXh0bgNhZW0CMTEAc3J0YwZhcHBfaWQMMzUwNjg1NTMxNzI4AAEenM2MxDiIxdeqmztCtf693Vjp0N71XVgyop4go1S3ju5ZiNbPmDBZ4PJbwrg_aem_CX_oDrNv1R6MvIoWyukkrw
Can companies seize your private property to build data center infrastructure?
According to legal scholar Aaron Walayat at the University of Dayton, it’s certainly a possibility.
In a new piece for The Conversation, Walayat warns that power companies in states like George and Pennsylvania have been considering the use of eminent domain — the government’s prerogative to seize land without its owners’ consent — to build more transmission lines used to power data centers.
If a landowner refuses a power company’s payout, the power company can turn to the local government to seize the land if it’s for “public use,” paying the landowner “just compensation.” These seizures are called condemnations, and most of the time they’re carried out by state and local governments, according to Walayat. In the case of transmission lines, the power company would be able to buy an easement on the landowner’s property.
But so-called “common carriers” like power and water companies can exercise this power too, he added, if governments delegate it. And while many states have placed heavy restrictions on how condemnations are used, courts have typically allowed entities like utilities and power companies to exercise it.
They’ve even allowed homes to be demolished in the name of “public use” and economic development.
Every state’s different, but the Maryland case illustrates that power companies will face plenty of obstacles if they want to just steamroll over people’s land. Walayat predicted that “arguments around whether additional transmission lines actually serve in-state customers may give landowners grounds for a challenge.”
Tomi Engdahl says:
Mad Men
OpenAI Appears to Be Missing Its Sales Goals by a Vast Margin
It’s a bloodbath.
https://futurism.com/artificial-intelligence/openai-ad-revenue-ai-advertising-financial-projection?fbclid=IwVERDUATTUP1wZG9mBWV4dG4DYWVtAjEwAHNydGMGYXBwX2lkDDM1MDY4NTUzMTcyOAABHuPdeBHCjPNxZ6AhFPwHrOEnpk1RaQ8nARSqpMLnjhNKLEbRQdE9wLlwF18Q_aem_JijwT7XlAxRwajkMFZTv8g
OpenAI wants you to believe that by 2030, it’ll be raking in $100 billion a year just from ads alone — even though it’s currently struggling to reach just $1 billion.
That massive gulf was observed in a new analysis from marketing consulting firm Emarketer, first flagged by AdWeek, which found OpenAI is on pace to undershoot its own five-year ad revenue projections by a whopping 90 percent. In fact, Emarketer’s take is even more devastating than that: it estimates the entire addressable market for chatbot advertising — the maximum amount of money up for grabs overall — at $5.4 billion.
That figure isn’t just bad news for OpenAI, but for every giant tech company, all of which are jockeying for a piece of the AI ad pie.
In 2026, Emarketer projects that the combination of OpenAI, Microsoft, Google, and Amazon will bring in under $1 billion in ad revenue. For context, OpenAI had projected that its AI ad revenue alone would hit $2.5 billion by the end of this year.
OpenAI needs three miracles to happen all at once. First, advertisers have to abandon decades worth of infrastructure built around search engines and social media and put all their advertising budgets into chatbots. Once that happens, OpenAI has to out-muscle previous ad-sales giants like Google and Meta, while the entire AI-ad market balloons from just a six-figure stream in 2026 to a raging, 12-figure river by 2030.
Tomi Engdahl says:
Bot for Teacher
Sex Doll Company Strikes Bizarre Deal to Put Its Robot in High School Classrooms
Who needs teachers when you’ve got… uh….
https://futurism.com/robots-and-machines/sex-doll-company-deal-robot-school-classrooms?fbclid=IwdGRjcATTvxFjbGNrBNO-5nBkb2YFZXh0bgNhZW0CMTEAc3J0YwZhcHBfaWQMMzUwNjg1NTMxNzI4AAEeA3jXYRlKJM6X2HlNGUeyjZNqXNFMcr37bjCBneHEfeXwkY5CjLYXqIBv7RY_aem_F6wcGF0SK5YZ5euQ8bDAcg
Robotics company Realbotix has long struggled to beat the allegations that its voluptuous humanoid robots are designed with prurient interests in mind.
Its $175,000 robotic companion, dubbed Aria, is platinum blonde, well-endowed, and tends to be decked out in tight-fitted sportswear at tech conventions. Yet the company insisted she’s not a sex doll, leading to plenty of incredulity online.
It’s also hard to ignore that Realbotix has an extensive X-rated past.
Now, as New York Focus reports, the Salamanca City Central School District in western New York is ready to dig deep into its budget and deploy one of the company’s humanoids, dubbed Sally, in the classroom. The AI-enabled robot will reportedly serve as a teaching assistant for high school students enrolled in STEM, and arts courses.
It’s hard not to see the company’s sex robot roots in Sally’s visage. The $57,000 android has smooth silicone skin, a dazed expression on her face, and an ill-fitting wig made of long brown hair.
The district’s superintendent Mark Beehler told New York Focus that he was willing to give up banning AI in the classroom since “students will find a way around most rules that schools put in place.”
“I also believe it is critical for schools to teach proper use of technology, not simply exclude it,” he said.
Sally’s onboard AI can be used to generate lessons, provide translations in real-time in over 100 languages, and provide human teachers with guidance if a “teacher loses their place during a lesson or needs a prompt on what comes next,” according to New York Focus.
To us, that sounds like a pretty cynical take on the future of education. Teachers are already facing a major uphill battle thanks to the advent of the tech, with students suffering from declining cognitive abilities.
Of course, Realbotix argues that it’s done its homework. Instead of hallucinating facts, a major shortcoming of the tech that makes it arguably unfit for most classroom use, Sally will allegedly say “I don’t know.”
In a press release, the Salamanca City Central School District stressed that the “Realbotix educational robot will never replace teachers, staff members, or meaningful human interaction.”
But whether Sally will actually serve as “another instructional tool that educators can use to engage students, reinforce classroom learning, and spark curiosity about emerging technologies,” remains to be seen
Tomi Engdahl says:
https://www.foodandwaterwatch.org/2026/06/24/ai-data-center-boom-farmland/?ms=some_fb_07082026_NAT-FWW-c3-data-center-ag-land-web-piece&oms=some_fb_07082026_NAT-FWW-c3-data-center-ag-land-web-piece&fbclid=IwdGRjcATT29JjbGNrBNPbunBkb2YFZXh0bgNhZW0CMTEAc3J0YwZhcHBfaWQMMzUwNjg1NTMxNzI4AAEebQCwr-FhErk6Z-aeAWmSMBW2tC8CRsXOjoJyZFm776Wkhic8W38GcKC5wWU_aem_jyvofpZJy0DxHHNhgRIIpw
Tomi Engdahl says:
https://www.tomshardware.com/tech-industry/artificial-intelligence/ai-data-center-developers-target-rural-territory-to-bypass-city-construction-bans-and-regulations-rural-locations-allow-sites-to-bypass-city-council-approvals-rezoning-votes-land-use-reviews-and-reduce-public-scrutiny?fbclid=IwVERDUATT3EJwZG9mBWV4dG4DYWVtAjEwAHNydGMGYXBwX2lkDDM1MDY4NTUzMTcyOAABHhoKMujgZqyr650I_fUILOQSHxKwj01H8dJIJ1h1KOPqa09nrHivSlurVh5g_aem_CgE5U1pfIBJxNI_QtSKZlA
Tomi Engdahl says:
Tell us all other health problems data centers cause.
All the medical misinformation from influencers is stored in data centers.
Tomi Engdahl says:
The claim on Chinese people gave invested money on spreading data center misinformation centers around a report titled “Foreign Influence in the Campaign against American AI,” published by the non-profit Bitcoin Policy Institute. The report alleges that networks funded by Neville Roy Singham—an American-born tech multi-millionaire/billionaire currently living in Shanghai—have spent millions of dollars promoting campaigns, digital media, and non-profit efforts opposing U.S. data centers and AI expansion.
https://www.wfmd.com/2026/05/18/report-chinese-propaganda-singham-network-foreign-dark-money-linked-to-campaigns-against-data-centers/?hl=en-US#:~:text=According%20to%20a%20new%20report%2C%20obtained%20by,Chinese%20propaganda%3B%20Chinese%20Communist%20Party%20state%20media%3B
Tomi Engdahl says:
Darrell Radabaugh Modern, highly automated hyperscale data centers operate on roughly 0.15 to 0.35 full-time operational workers per megawatt. With older data centers it was around 1 person per megawatt.
https://hamminstitute.org/site-files/documents/data_center_workforce.pdf?hl=en-US#:~:text=Workforce%20intensity%20varies%20sharply%20by%20facility%20scale.,*%201.%20Benchmark%20Summary%20by%20Facility%20Size.
Tomi Engdahl says:
Jason Smith The current internet works well because capacity was built ahead of demand. Data usage isn’t static; it grows every year as video resolutions increase (from 1080p to 4K/8K), security protocols become heavier, and more everyday devices connect to the web. Without continuous scaling, existing facilities would reach capacity, leading to slowdowns, higher latency, and outright outages during peak hours. Even if you personally don’t use tools like ChatGPT or image generators, AI integration is happening at the structural level.
Tomi Engdahl says:
Major AI developers (including Microsoft, Google, Meta, and Amazon) are projecting that AI computing capacity must scale dramatically over the coming years—with global data center capacity expected to roughly double by 2030—to handle the exponential rise in continuous, complex AI workloads. Without building these purpose-built facilities, existing digital infrastructure would face severe bottlenecks, stalling further AI development and deployment.
Tomi Engdahl says:
Jason Smith Major AI developers (including Microsoft, Google, Meta, and Amazon) are projecting that AI computing capacity must scale dramatically over the coming years—with global data center capacity expected to roughly double by 2030—to handle the exponential rise in continuous, complex AI workloads. Without building these purpose-built facilities, existing digital infrastructure would face severe bottlenecks, stalling further AI development and deployment.
If those are not built, the projected payback for huge AI investment will not happen. That hits the core of what Wall Street, tech executives, and venture capitalists are fiercely debating: The AI Return on Investment (ROI) paradox.
the entire financial model for “Generative AI” and “Artificial General Intelligence” relies on a direct relationship between compute infrastructure and revenue generation.
If the new facilities aren’t built, the financial payback model fails.
The Pro-Build View: Infrastructure is the Revenue Bottleneck
From the perspective of companies like Microsoft, Meta, Google, and OpenAI, compute capacity is currently the ceiling on their revenue.
The Skeptic’s View: Overbuilding Destroys the ROI First
A growing number of financial analysts (including major reports from Goldman Sachs, Bain & Company, and MIT) argue that the ROI model is already broken—and that building more data centers will actually make the payback worse.
Tomi Engdahl says:
Summary: A Classic Catch-22
The tech industry finds itself in an economic high-wire act:
If they don’t build – new software revenue growth dead on tracks
If they build – risk huge investments that might not be ever pay back
Because major tech firms are more terrified of being left behind than overspending, they are choosing to overbuild—hoping that the software applications and revenue models will catch up to the physical infrastructure before the capital runs out.
Tomi Engdahl says:
The White House is attempting a high-stakes balancing act: aggressively encouraging domestic data center growth to secure global technological leadership, while simultaneously trying to contain the domestic political fallout from soaring local energy demands and community opposition.
Tomi Engdahl says:
Roughly 40% of all U.S. data centers sit in areas experiencing high or extreme water stress (such as Phoenix, Arizona, and North Texas), where evaporative cooling directly competes with residential drinking water during summer droughts.
Tomi Engdahl says:
So before everyone starts blaming new AI apps and such.
Remember that your phone that uses autocorrect… That’s AI.
When it uses predictive text… That’s AI.
When you Google ANYTHING… AI.
When you use Google Maps… AI.
Any maps app… AI.
Any app on your phone… AI.
So… Hate to break it to you. Anyone basically using Siri, Alexa, anything with “smart” anything. Is using AI. You’re all guilty. Just like me.
Tomi Engdahl says:
While putting solar panels on the flat roofs of massive data centers seems like a no-brainer, three physical and structural realities explain why rooftop solar provides surprisingly little relief:
1. The Energy Density Mismatch
The Math: A commercial solar panel generates roughly 15 to 20 watts per square foot during peak daylight. Even if you cover every single square inch of a data center roof with solar panels, it generates less than 2% to 5% of the power the servers inside consume.
2. The Roof Is Already Full
Adding solar panels means squeezing them into the gaps between hot air exhausts, which lowers panel efficiency due to thermal heat, or structurally reinforcing the roof to elevate panels above heavy equipment.
3. Intermittency vs. 24/7/365 Demand
Data centers cannot throttle down when a cloud passes overhead or when the sun sets at night; they require continuous, high-density baseload power every second of the day. Rooftop solar generates peak energy for about 4 to 6 hours a day and zero at night, requiring massive battery banks if used directly off-grid.
Tomi Engdahl says:
The reality is that AI is already deep inside the judicial system.
Over 60% of US federal judges and chamber clerks now use legal AI tools (like Westlaw AI or Lexis+) to summarize mountain-sized case filings, review discovery documents, and draft initial opinion outlines.
Tools like COMPAS and PSAs (Pretrial Risk Assessments) process historical data to give defendants a “risk score” predicting whether they will miss court or reoffend.
Prosecutors and defense attorneys use AI to process thousands of hours of bodycam footage, run facial recognition, and flag key phrases in phone records or emails.
The shift toward algorithmic tools raises serious constitutional and ethical dilemmas
Tomi Engdahl says:
Here is another hoax: Anti data center hysteria is organic.
Tomi Engdahl says:
https://law.stanford.edu/pretrial-risk-assessment-tools-factsheet-project/
Tomi Engdahl says:
https://en.wikipedia.org/wiki/COMPAS_(software)
Tomi Engdahl says:
https://news.northwestern.edu/stories/2026/03/northwestern-study-finds-a-significant-number-of-federal-judges-are-already-using-ai-tools
Tomi Engdahl says:
When lawyers use generative AI without double-checking its work, things usually go wrong in very specific—and often hilarious—ways. What starts as a quick shortcut ends with a judge asking why the cited precedents do not actually exist. The most notorious way AI fails in legal practice is by hallucinating case citations. This happens around the world
https://thebarristergroup.co.uk/blog/ai-made-a-legal-mistake?hl=en-US#:~:text=The%20case%20of%20Mata%20v%20Avianca%2C%20Inc.,decisions%20did%20the%20fabrication%20come%20to%20light.
https://www.theguardian.com/law/2025/sep/03/lawyer-caught-using-ai-generated-false-citations-in-court-case-penalised-in-australian-first?hl=en-US
https://youtu.be/HXoOb96_92U?is=WZx5X2sxKdyHv4Yq
Tomi Engdahl says:
What does it feel like when an AI version of you takes your job? That’s been the reality some micro drama actors have been facing.
(Credit: MoboReels)
#AI #actors #techWhat does it feel like when an AI version of you takes your job? That’s been the reality some micro drama actors have been facing.
#AI #actors #tech
They starred in shows. Then AI actors ripped off their performances. : https://mrf.lu/2cjnp
Tomi Engdahl says:
“The operation of more than a million data center satellites threatens potentially catastrophic forms and quantities of atmospheric pollution, risking damage to the climate, to the ozone layer, to human health, and to the chemistry of the stratosphere itself.” https://trib.al/qMo1ajF
Shot Down
The Type of Orbital Data Centers That Billionaires Want to Launch Into Space Would Wreak Ecological Catastrophe, Scientists Warn
“The operation of more than a million data center satellites threatens potentially catastrophic forms and quantities of atmospheric pollution, risking damage to the climate, to the ozone layer, to human health, and to the chemistry of the stratosphere itself.”
https://futurism.com/space/orbital-data-centers-billionaires-ecological-catastrophe-petition?fbclid=IwdGRjcATUbn9jbGNrBNRuX3Bkb2YFZXh0bgNhZW0CMTEAc3J0YwZhcHBfaWQMMzUwNjg1NTMxNzI4AAEeb8dD7Og8xz2tGF94Q-9of3aI9FeHhIDxRaKx-YshyYZkjKp89NZec94XlFI_aem_uJ57IXoAZqHKQtMd2JSX_g
Over the past year or so, a puzzling idea has taken hold among billionaires ranging from Elon Musk to Jeff Bezos: that instead of trying to force data centers on communities that don’t want them down on Earth, it would be much easier just to launch them into space.
The economics and logistics of the scheme, many experts have pointed out, are absolutely absurd. And even beyond those practical concerns, if corporations actually did somehow manage to fill the planet’s orbit with the facilities, scientists are now warning that the environmental cost would be devastating.
A new petition organized by the group EarthJustice, first reported by the Guardian, is warning of “catastrophic” consequences for the planet if the billionaire-backed dream ever came to pass. The 29-page petition calls on the US Federal Communications Commission to investigate current orbital data center licensing requests as potentially in violation of “federal law,” joining the chorus of experts warning that it’s a horrible idea for just about everybody.
“The FCC is currently considering multiple requests for licensing extraordinary numbers of satellite-based data centers to be placed into low-earth orbit over the next decade,”
Tomi Engdahl says:
An ex-programmer’s devastating take on AI data centers is going viral — and it’s hard to ignore
https://www.techradar.com/ai-platforms-assistants/an-ex-programmers-devastating-take-on-ai-data-centers-is-going-viral-and-its-hard-to-ignore
A local planning meeting speech is going viral for exposing the real cost of AI infrastructure
A former programmer’s anti-data-center speech is going viral because it cuts through AI hype and focuses on local costs
Ohio has become a hotspot for backlash over data centers, with concerns over power, water, land use, and tax breaks
The bigger question is whether communities are being asked to sacrifice too much for too little in return
Tomi Engdahl says:
https://www.facebook.com/share/p/1EDcxvY2Fi/
AI Data-Center Water Crisis?
https://youtu.be/-nHVjYalRFw
How much water do AI data centers actually use?
“AI data centers are part of a financial bubble; too many are built now, but they consume less water than agriculture and farming. Unless they’re connected to already limited municipal water supplies.” – Fabio Ciucci, LinkedIn Post.
But if you analyze the water consumption numbers for data centers, you’ll be surprised because it’s actually not a water problem but an energy source problem.