The U.S. Department of Energy recently announced that it is turning old federal land — including Cold War uranium sites, closed military facilities, and other public parcels — into part of the physical backbone of America’s artificial intelligence buildout, pairing new data centers with the power generation needed to run them. The projects could also create new domestic jobs.
Critics will focus on the benefits to big technology companies. The larger issue is harder to dismiss: Energy security is national security. The country that can build and power the next generation of AI infrastructure will hold an enormous economic and strategic advantage.
Whatever disagreements Americans have over individual energy sources, China is not waiting for us to resolve them.
That means the United States cannot afford an ideological energy policy. Whether the resource is natural gas, nuclear power, solar, battery storage, or the critical minerals needed to build advanced technologies, domestic supply should be treated as a strategic asset.
AI is already changing the scale of America’s power needs. Data centers alone could soon consume as much electricity as the entire country of Malaysia. Advanced manufacturing is returning to American soil and will require still more reliable power.
The military is modernizing with increasingly energy-intensive technology as well. As retired U.S. Air Force Lt. General David Deptula argued in the Washington Post, data itself has become a strategic military asset. The countries that lead the next generation of AI will need more than talented engineers and sophisticated algorithms. They will need the infrastructure to power the entire ecosystem.
China understands this. Beijing has spent years pursuing an aggressive all-of-the-above energy strategy. It continues to build coal plants while investing heavily in solar, nuclear power, hydropower, and battery storage. Whatever disagreements Americans have over individual energy sources, China is not waiting for us to resolve them.
The Energy Department’s plan is therefore a timely step. It creates opportunities to pair new power generation with the infrastructure that will consume it. But if America intends to win the AI race, policymakers across the political spectrum will have to go further and remove unnecessary obstacles to new energy supply.
Solar power, for example, has been the fastest-growing source of new U.S. electricity generation for five years running. In 2025, the United States added 43 gigawatts of new solar capacity, enough to power over 32 million homes. Where permitting and regulatory barriers needlessly delay viable projects, Washington should remove them.
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The same urgency should apply to critical minerals. The United States has spent years allowing dependence on foreign supply chains to deepen even as minerals became indispensable to batteries, electronics, defense systems, and energy infrastructure. Domestic mining and processing cannot expand at the speed national security demands if projects spend years trapped in permitting and regulatory limbo.
This is not an argument for replacing traditional energy with newer technologies. It is an argument for abundance. Oil and gas remain essential. Nuclear power can provide large amounts of reliable electricity. Solar and storage can add capacity quickly in the right places. Critical minerals underpin all of them. The strategic question is not which source wins an ideological contest. It is whether America can produce enough energy, reliably and affordably, to meet the demands ahead.
China is already acting on that logic. The United States should do the same. The next phase of economic and military competition will be shaped not only by who invents the best technology, but by who can build the plants, mines, transmission, data centers, and generation needed to deploy it at scale.
The Energy Department’s announcement is a good start. Now we need to make abundance the policy: build more, permit faster, secure domestic supply chains, and stop treating energy sources as political footballs.
America will need all the reliable energy it can produce, however we can produce it. The country that powers the future will have a much better chance of leading it.
A dinosaur logo is at the center of controversy surrounding the whereabouts of some rare literature.
This story, involving Amazon, has taken wild cross-country turns and led to one of the most unexpected places.
'They just want the content as a bunch of words strung together.'
As AI companies have rushed to gobble up texts for digitization and model training, suspicion has mounted that companies are buying up batches of rare tomes for uses they'd rather keep under wraps.
When it comes to Amazon, the granddaddy of Big Tech book merchants, the narrative starts with one specific shipment of 1,000 books.
Described as having been printed in small batches or obscure languages, the thousand were purchased through an online marketplace called Biblio.
A journalist from 404 Media, piquing his curiosity, asked the seller to help him puzzle through what he described as an anomalous "historical spike" in book sales the past few years. According to Publishers Weekly, book sales increased in 2025 by 2.5% over 2024.
404 decided to affix one of the books with an Apple AirTag — effectively a tracking device — in order to find out who was behind the large purchase.
It worked.
The shipment went to a California airport before winging its way to Milwaukee International Airport. The same day, the AirTag showed that it went on to a warehouse belonging to Trifinity, a specialized shipping and distribution company in Kenosha, Wisconsin.
It stayed there for two weeks before traveling west by truck to Colorado. And then, the next day, it arrived at an Amazon warehouse in Las Vegas.
At Amazon Fulfillment Center LAS8, as the warehouse's location is known, Amazon is allegedly collecting, scanning, and badly damaging rare books to train its AI model, all through a team called VGT3. In vaguely military fashion, VGT3 has a patch-like logo: a tyrannosaurus rex baring its teeth over an open book.
The details on book-hungry VGT3 were previously undisclosed until recent reporting, although there have been some online breadcrumbs. On a Reddit thread under AmazonFC from last year, one person said they work at VGT3 and all they do is "scan books."
Amazon has not publicly explained VGT3's scope or operations.
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Reporting the revelations, 404 Media alleges that Amazon is buying a massive number of books, scanning them to train their AI model, and effectively destroying them in the process, cutting off the spines to make them more easily scannable.
"Some are assigned to cut books, and others go to receive where they get books and scan the bar codes," an alleged employee told 404. "We didn't have rates, but now we do, but it's not stressful."
The systematic scanning of the codes, known in the trade as ISBN numbers, further fuels speculation that the world's books are being methodically scanned by tech companies ultimately intending to consume printed material so thoroughly as to retire it from common use.
Blaze News reached out to Amazon to ask if the books are being scanned to train an AI model, if there is public information about VGT3, and if the books are indeed being destroyed.
In response, an Amazon spokesperson only told Blaze News that the company "purchases books through commercial channels to help develop and improve the products and services our customers use."
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The scope of the rare books were described as being prints that not many people would care about "in the same way people might care about the first edition of 'Oliver Twist.'"
"There are different types of value," said the bookseller who sent out the bulk shipment. "There's monetary value, obviously, but there are a lot of other types of value."
Without identifying the books by name, the seller claimed they offered "historical value, intellectual value, [and] sentimental value. All sorts of things, and all of those the AI companies don't care about. They just want the content as a bunch of words strung together."
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The hits just keep on coming in a recent court case that relied on expert testimony.
Lawsuits stemming from a 2020 industrial disaster have had plaintiffs, family members, and defendants pointing fingers at each other, with varying results. However, a discovery in one of the lawsuits turned everything on its head in a matter of just a couple of hours.
'I have no idea how it works.'
The story comes from the Watson Grinding explosion that happened roughly six years ago in Houston, Texas.
A massive explosion killed three people and injured dozens, ABC 13 reported, due to faulty equipment. Federal authorities determined the explosion was caused by a "degraded and poorly crimped rubber welding hose" that leaked the flammable gas propylene throughout the building overnight.
Massive industrial company 3M was hired to inspect and maintain the gas detection systems that allegedly failed at Watson Grinding, leading to a huge lawsuit from victims against the company.
According to 404 Media, 3M hired one Josh Autenrieth from KnightHawk Engineering to prepare an expert witness report about the explosion. During questioning, one of the plaintiffs' lawyers noticed a document from the defense that appeared to have been AI generated, and according to the court transcript, he simply searched its content to find that Autenrieth's ChatGPT prompts were all available online.
"Well, do you realize, sir, that your chat right now is still publicly available?" the lawyer says in the transcript.
"I have no idea how it works," Autenrieth said in response.
The deposition was paused for three hours to gather all the prompts. This revealed a treasure trove of ChatGPT content that is still publicly available online, where Autenrieth had the AI develop his report nearly entirely.
"I am being retained as a professional expert witness by 3M in defense of them in their lawsuits," the first prompt read. "I need to create an expert witness report to defend 3M's standard of care for their work in calibrating and commissioning (return to operations / RTO) the iTrans gas detectors. I need to show that 3M met the standard of care and why."
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Shockingly, after uploading hundreds of documents for the chatbot to review, the user asked the AI to "show how 3M is 0% at fault for the explosion at watson grinding."
Unsurprisingly, the report draft concluded that "3M met the applicable standard of care" and was "0% responsible for the January 24, 2020, explosion."
Attorney Will Moye told 404 Media that the expert "relied on AI not as an assistive device, but exclusively relied on ChatGPT to form his opinions and write his report."
"He acknowledged [at trial] the prompts he put in were biased toward 3M to help 3M win the case […] it's really egregious,” Moye added.
It was also revealed through court documents that Autenrieth billed his company for at least 174 hours in the case. He said that he is salaried but that his work has a $475 per hour rate. This totals at least $82,650 of work.
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Nathan Knight, vice president of KnightHawk Engineering, told Blaze News in response that Autenrieth utilized AI as only a tool and stands behind his work. Knight further described isolated questions and excerpts from the trial as "fake news" that does not provide the complete story.
His comment, in full, is below:
AI is a tool that is used extensively in today's work environment, and its use will continue to increase as technology advances. Mr. Autenrieth utilized this technology as a tool to assist in reviewing questions, arguments, and counterarguments related to the case. AI did not replace his engineering judgment. Mr. Autenrieth developed and presented his own professional opinions and stands behind those opinions.
What has been presented is a selective and negative snapshot that, without the complete context, can fairly be characterized as "Fake News." Looking at isolated questions or excerpts does not tell the complete story of the analysis, the expert report, or what was ultimately presented in court.
The opposing side challenged Mr. Autenrieth's qualifications and attempted to prevent him from offering his opinions. Those challenges were unsuccessful, and Mr. Autenrieth was permitted to testify and present his professional opinions to the jury.
Technology continues to advance, whether we like it or not, and AI is here. Engineers and other professionals will increasingly use modern tools to assist them in their work. What matters is that the professional evaluates the information, exercises independent judgment, and takes responsibility for the opinions ultimately presented. Mr. Autenrieth did exactly that.
KnightHawk stands behind the professionalism and integrity of its engineers. We strongly disagree with any characterization suggesting that the selective use of AI excerpts somehow replaces or invalidates Mr. Autenrieth's independent engineering judgment or professional opinions.
Last week, a Harris County jury awarded $61.5 million to 24 plaintiffs in the case, one of several verdicts that have come against 3M.
In June 2025, $38 million in damages was awarded to five victims of the explosion, while another $118 million was awarded to seven victims in November 2025.
3M did not respond to Blaze News' request for comment.
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AI wearables, like Meta’s Ray-Ban glasses, may be convenient, but at what cost — and not just to the wearer but to the surrounding public?
Unlike cameras and phones, which “announce" themselves, says Glenn Beck, AI wearables go practically undetected — which raises the issues of consent and privacy.
But this tension is not new.
Glenn notes that early photography required subjects to “hold still … 30 seconds,” so permission was built in. Then came the first true hidden cameras — “detective cameras” worn under a vest with the lens shaped “to look like a button.”
Shortly after, George Eastman’s small box camera arrived and made candid snapshots easy. The public backlash was fierce: beaches and the Washington Monument banned them, and papers called carriers “Kodak Fiends.” Within two years, Boston lawyer (and future Supreme Court justice) Louis Brandeis argued for “the right to be left alone” — a right that, as Glenn points out, “is not in the Constitution” but had to be invented “because of cameras.”
But what we’re dealing with today with AI wearables is “much worse,” he says.
“You are trading the right to be misunderstood in private now,” he says, pointing to CNN Business tech editor Lisa Eadicicco’s experience with her Amazon Bee Pioneer bracelet, which decided a casual comment about moving meant she was “anxious” about stability — even though she wasn’t.
“Now that conclusion exists in a file somewhere in a company's system, and it will inform the next inference and the one after that, and it will store it,” says Glenn, describing how AI wearables’ conclusions about gathered data — even if it’s incorrect — will become part of the wearer or bystander’s “record.”
When one’s “off-the-record” self is eradicated, the result is that everyone becomes circumspect and reticent.
“In a room where everything is recorded and then held by a private company, that's a room where nobody's saying anything out loud. Nobody's thinking out loud. Nobody's risking anything,” says Glenn.
“A recording,” he explains, is “evidence — and evidence can get subpoenaed.”
“And it may be false evidence!” he exclaims.
“Every conversation you will ever have will be indexed and searchable … and it will be sitting on a server owned by a company with lawyers who work for the company,” Glenn continues.
But despite the devastating blows to privacy and consent, Meta CEO Mark Zuckerberg’s pitch for AI-powered smart glasses, he explains, has essentially been: “Wear it, or fall behind.”
Right now, the risk of declining AI wearables is low, says Glenn, but a day is coming soon when life will become nearly impossible without them.
“Two years from now, when your team's meeting has notes, action items, performance reviews, and they're all running off transcripts, declining won't be a preference any more,” he warns. Now “it's a problem; it's you being difficult. Nobody will forbid you. They'll just build the office around the assumption and let the cost fall on the holdout: you.”
To hear more, watch the video above.
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A massive system has been built to replicate how humans react to products, apps, and websites, without needing humans at all.
Researchers at Harvard University and Massachusetts Institute of Technology say their network has the ability to simulate the world with "persona agents."
'The agents successfully expressed ... their assigned traits 91.5% of the time.'
Based off a core set of just under 600,000 "human-grounded" personas, coupled with 400,000 synthetic records, the group at MatrAIx says they have found a way to simulate real reactions to questions, products, and more.
The approximately one million personas were used as the basis to create an AI bot population of 8.3 billion, which MatrAIx says can be run like a simulation and act as one giant focus group.
This allows companies to use the simulated personalities to garner reactions to price changes, for example. MatrAIx tested this theory by running its simulation to see whether or not one million people would still buy a 12-pack of Coca-Cola after a $2 increase. The simulation determined 61% of the population still would.
In addition to evaluating hesitation after a price increase, the bots simulated willingness to continue after an AI assistant fails its task as well as latency tolerance for websites, meaning how long a person will use a slow website before abandoning it.
Other examples provided included evaluating a mental health chatbot or shopping on Amazon for an espresso machine under $200 to see which product the AI bots choose and why.
The approach extends to social media apps. Instagram was used as an example where a bot can search for recipes and then watch and save preferred videos. It was explained that the program could have millions of bots doing this at the same time.
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There's just one problem. The agents in the massive simulation cannot be wholly trusted to act the way humans would. As with any AI agent, there is a possibility that an agent in the world sim could fail to perform as instructed or desired.
In Harvard's controlled study of 400 trials, measuring the bots' adherence to 10 behavioral attributes, the results were good but not perfect. "The agents successfully expressed or correctly suppressed their assigned traits 91.5% of the time," the researchers wrote.
MatrAIx, headed by Xiaomin Li (Harvard) and Yuexing Hao (MIT), conducted over 16,000 evaluation trials across eight different types of tasks. They used three large-language models for their studies: Claude Opus 4.8, Chat GPT 5.5, and Claude Haiku 4.5.
Human evaluations of the persona quality, however, were actually lower, listed as an average of 4.135 out of 5, which equates to about 83%.
This roughly 8.5% rate of agents simply failing to adhere to a persona could have large implications for customers who use the bots on a large scale. In the example provided for Coca-Cola consumption, that carries the possibility of 85,000 bots not answering accurately.
But the deeper problem the study confirmed is that Earth's billions of human beings can't be accurately simulated by AI agents programmed to be well-behaved. It's impossible to model and predict human behavior if the agents standing in for the humans aren't allowed to behave in all the devious, dangerous, and flawed ways individuals and groups do.
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That raises the dark prospect that entities or governments seeking ultimate predictive power will have to build large-scale simulators where agents representing real people are allowed to have antisocial, criminal, sinful, or even evil traits and behaviors.
The alternative, deeper human research, is nowhere near as cheap and swift as AI modeling. Most research groups seem to say that human focus groups are not effective at garnering mass public appeal anyway, while at the same time surveys can be a bit more time-consuming. The trade-off is that they are still human.
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Until now, Google Gemini has been an optional part of Android. Most of its features are locked behind the dedicated Gemini app, or you can choose to rely on Google Assistant as your on-device companion for fielding questions and completing tasks. That is all about to change, though, as Google officially prepares to retire its old assistant for an AI future, and it is coming sooner than you think.
Google brought Gemini to Android in early 2024. Since then, the company has progressively injected its AI into every corner of its operating system. The latest iteration, Gemini Intelligence, aims to take its chatbot a step farther by giving it agentic capabilities. At launch, the only way to set Gemini as your default personal assistant instead of Google Assistant was to manually make the switch in your settings. Many newer phones, however, default to Gemini straight out of the box.
You aren’t allowed to delete it from your phone. You can, however, take away its functionality.
Needless to say, if you have avoided Gemini like the plague thus far, your efforts are commendable, but your luck is about to run out.
Starting on September 4, Google will start rolling out Gemini support as the default personal assistant in all applicable Android models — devices with 2 GB of RAM or more that run on Android 9 or later. The process will take several weeks to reach everybody, so you may not lose access to Google Assistant immediately. However, once it is complete, Gemini will take over as the default assistant on your handset, whether you like it or not.
It’s not just your phone, either. The switch is coming to all devices in Google’s product ecosystem, including tablets running Android, car infotainment systems with Android Auto, smartwatches running on Wear OS, and TVs with Google TV or Android TV. In other words, you can’t escape it … but you might be able to turn it off, if you know where to look.
To disable Gemini on a Samsung Galaxy device, open the Settings app, select “Apps” near the bottom of the page, and tap “Choose default apps” at the top. From there, tap “Digital assistant app,” and choose either an alternative to Google or select “None” from the options. Now, when you invoke the digital assistant on your phone, absolutely nothing will happen. Your digital assistant is effectively gone.
For Google Pixel phone owners, open up the Settings app and choose “Apps” near the top of the page. Next, select “Default apps,” followed by “Digital assistant app,” and finally, choose “None” or an alternative option to Google, if applicable. Congrats, now your phone no longer has an AI-powered digital assistant!
If you use an “other” branded Android phone, such as a Motorola, OnePlus, Nothing, etc., the process should be similar to the steps above. The main goal is to find the default apps section in your settings and change the digital assistant to anything other than Google. Once you do that, you’re free from Gemini! Well, sort of. There’s more …
Google has also baked Gemini into many of your favorite apps, including Gmail, Maps, and Drive, but this should only work if you have Personal Intelligence enabled. To check, open the Gemini app on your phone, select “Personal Intelligence,” and then “Connected Apps.” From here, uncheck every app and service that’s enabled. There are a lot of integrations on this page, so make sure you scroll all the way to the bottom and get every single one.
Now that we’ve fired Gemini from its digital assistant role and banished it from Google apps, there’s one last thing to do, and this one comes with an unavoidable caveat.
Some new phones these days, especially from Samsung and Google, come with the Gemini app installed by default, and you aren’t allowed to delete it from your phone. You can, however, take away its functionality.
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To disable Gemini on Android, simply swipe into your app drawer and locate Gemini in the app list. Hold your finger on the app for several seconds to bring up the secondary menu, and choose the “i” icon that indicates “App info.” Next, tap on the “Disable” switch. You’ll get a warning message to try to convince you to change your mind. Ignore that, disable the app anyway, and you’re all set. You will no longer see Gemini in your app drawer, and it will cease to work.
As expected, it’s not easy to pry Gemini’s grubby claws out of an Android device. The service is ubiquitous, and as Google triples down on its AI strategy, it will only become more prevalent throughout its operating systems. However, if Gemini is not something you want anywhere near your phone and your data, these steps will help you reclaim some of your privacy and peace of mind.
Artificial intelligence has become a national political issue and increasingly a local one. Communities across the country are fighting over the massive data centers needed to power the AI boom. Environmental groups warn about water consumption. Ratepayers worry about electricity bills. Workers fear the technology will undermine their livelihoods.
The backlash crosses ideological lines, and many of the concerns deserve to be taken seriously. But too often, the debate begins and ends with a terrifying number stripped of the context needed to understand it.
As AI advances, America will face difficult choices. The only way to make them intelligently is to start with the facts rather than with numbers selected for maximum panic.
There are genuine questions surrounding AI — privacy, surveillance, censorship, individual autonomy, and concentrated power among them. But three of the most common criticisms of AI and data centers are often overstated.
Stories about data-center water use often begin with numbers designed to shock. One project may use millions of gallons a day. Another state may be projected to consume billions of gallons annually. In a water-stressed community, those figures can absolutely matter.
But scale matters too. A 2026 analysis published by the Florida Water and Pollution Control Operators Association estimated that all U.S. data centers combined accounted for roughly 0.3% to 0.4% of total daily U.S. water withdrawals, based on 2021 figures.
Cooling methods also vary dramatically. Some facilities rely heavily on evaporative cooling. Closed-loop and air-cooled systems can use far less water. Location, water source, cooling design, and the condition of the surrounding system matter enormously.
Industrial comparisons help restore perspective. Data centers are hardly unique in consuming large volumes of water. U.S. golf courses use roughly 30 times as much water annually, while California almond production alone has been estimated at well over 100 times as much.
That does not mean a poorly located data center cannot strain a local supply. It means “millions of gallons” is not an argument by itself. The relevant question is whether a particular facility imposes a meaningful burden on a particular water system.
The electricity numbers are enormous too. Lawrence Berkeley National Laboratory estimated that U.S. data centers consumed about 200 terawatt-hours of electricity in 2025, roughly 4.7% of total national electricity consumption.
From there, critics often assume that more data-center demand must translate directly into higher household bills. The evidence is less straightforward. Some research suggests that recent data-center growth has had only a limited effect on retail rates, while broader inflation and energy-policy choices may explain more of the increase consumers have seen.
That does not mean new data centers are costless to the grid. Poor rate design can shift infrastructure costs onto ordinary customers, and badly planned projects can strain local capacity. But the obvious answer to rising demand is not simply to suppress demand. It is to build more abundant, reliable power.
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The AI boom may be creating exactly that incentive. Amazon recently acquired an 8,000-acre site in Texas for a data-center project that could include up to 7.65 gigawatts of on-site natural-gas generation. Microsoft, meanwhile, signed a deal tied to the restart of Three Mile Island to supply roughly 835 megawatts of nuclear power.
America spent decades making it harder to build reliable energy. If AI demand helps reverse that habit, that is not obviously a national disaster. It may be the pressure needed to start building again.
Of the three claims, job displacement deserves the most caution. I have written before about the real possibility that AI could eliminate certain jobs, especially entry-level positions. Long-term forecasts are difficult because nobody knows how capable these systems will become. Still, history gives us reason to distrust the most apocalyptic predictions.
In 2016, AI pioneer Geoffrey Hinton argued that people should stop training to become radiologists because machines would soon outperform humans at reading medical images. A decade later, radiology is hardly disappearing. Research shows the number of active U.S. radiologists rose over the past decade, salaries increased, and workloads expanded along with the use of medical imaging.
That may be an example of “Jevons paradox”: When technology makes a resource or service cheaper and more efficient, total demand can rise. A recent medical paper applied the idea directly to AI and physicians.
The same possibility applies beyond medicine. If AI makes a programmer five times more productive, it is tempting to assume the economy will need one-fifth as many programmers. But economies are not static. If software becomes dramatically cheaper to produce, businesses that could never afford custom software may suddenly buy it. New applications become economical. Entirely new product categories can emerge.
None of that guarantees that every displaced worker will land comfortably in a new job, or that every profession will grow. Technological change creates winners and losers. The point is narrower: Productivity gains do not translate mechanically into equivalent job losses.
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None of this means AI is safe or harmless. The strongest concerns may simply be different from the ones dominating the headlines.
As AI becomes embedded throughout society, these systems could shape what information people see, how institutions make decisions, and how individuals interact with government and business. Massive data collection could strengthen surveillance. Ideological biases could be embedded in algorithms. Dependence on AI could weaken personal autonomy and concentrate decision-making power in governments and corporations.
Those questions deserve more attention than sensationalized claims about water, watts, and workers.
As AI advances, America will face difficult choices. The only way to make them intelligently is to start with the facts rather than with numbers selected for maximum panic.
The goal should be to preserve individual liberty, privacy, transparency, personal autonomy, and constitutional principles while allowing innovation to flourish. Exaggerating the easy concerns only makes the difficult ones harder to confront.
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