© Nicole Craine for The New York Times
Ever find something you want to buy online, leave it sitting in a browser tab and then completely forget where you saw it? Maybe you spotted a great pair of headphones while searching Google. Later, you found a birthday gift at another retailer. Before long, you've got a dozen tabs open and no idea which store had the better deal.
Google thinks it has a solution. On Oct. 15, the company began the U.S. rollout of Universal Cart, a new artificial intelligence-powered shopping tool that brings products from different retailers into one place. It also tracks prices, watches for restocks and helps you find savings before checkout.
With holiday shopping approaching, the timing could be especially useful. But there's another question worth asking. Will having everything in one cart help us spend less, or simply make it easier to buy more?
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AMAZON ABOUT YOU MAY KNOW YOU A LITTLE TOO WELL
Google Universal Cart is a shopping hub that works across Google Search and the Gemini app. Instead of keeping separate lists of products you might buy, you can save items from different retailers in one place. For example, you might find a coffee maker while searching Google and add it to your Universal Cart. Later, while talking with Gemini about gift ideas, you could save a pair of sneakers from another store. When you return, both products will be waiting for you. Google first previewed the tool in May 2026. Now, Universal Cart is rolling out to U.S. shoppers. It uses Google's Shopping Graph, which contains more than 60 billion continually refreshed product listings. That information helps the system monitor prices and availability across supported products.
The biggest attraction here is convenience. But Google has added several features that could also help you avoid paying more than necessary.
Shopping online often means bouncing between websites. You find something at Target, check another item at Walmart and then head to Sephora for a gift. Remembering where you saw everything can become a chore. Universal Cart lets you save supported products you discover through Google Search and Gemini. More importantly, your saved items stay together when you return to shopping. That could come in handy when you're shopping for several people or making a big purchase that requires some research. You can keep your options organized without committing to buying anything right away.
Here's the feature I find particularly interesting. Universal Cart can monitor saved products and notify you when a price drops. It can also alert you when something that sold out becomes available again. Suppose you're considering a new television but aren't ready to spend the money. Rather than checking the same retailer every morning, you can save it and let Google's shopping system watch for changes. The alerts could be especially helpful heading into Black Friday and the holiday shopping season. Still, remember that a price reduction doesn't automatically guarantee the lowest price available.
IDENTITY THEFT PROTECTION IS CHANGING: WHAT TO LOOK FOR
This is where Google's AI starts doing some extra work. Universal Cart can surface relevant promotional codes and consider benefits associated with your payment cards. Let's say you have multiple credit cards but can't remember which one offers better rewards at a particular retailer. Universal Cart uses information from Google Wallet to understand supported credit card benefits and help you choose between payment methods. It can also show relevant promotional codes directly in your cart, potentially helping you find savings you might otherwise miss. However, I would still check the details before choosing a card. Rewards programs come with conditions, and the highest points offer may not always translate into the greatest savings.
Once you're ready to buy, Universal Cart offers a more streamlined checkout experience with participating retailers. In some cases, you can complete the purchase using Google Pay directly from the cart. Alternatively, Google can transfer your selected items to the retailer's website so you can finish your order there. Google says its simplified checkout experiences include retailers such as Nike, Sephora, Target, Ulta Beauty, Walmart and Wayfair, along with many Shopify merchants. However, the available checkout options depend on the retailer. Either way, the retailer remains the seller of record and handles order confirmations and customer support. That means you'll continue dealing with the merchant for delivery questions or returns.
119,000 FAKE SHOPS COULD STEAL YOUR CREDIT CARD DETAILS
Google began rolling out Universal Cart to U.S. users on Oct. 15. The feature works across Google Search and the Gemini app, although availability may vary as the rollout continues. To explore it, open Google Search or Gemini and look for products you're interested in buying. When Universal Cart becomes available in your shopping experience, you can save supported products from different retailers. Google says those items will remain in your cart when you return, allowing you to pick up where you left off. You can also use the cart to monitor price changes, discover promotional offers and review available checkout options. However, Google hasn't provided a single set of instructions that applies to every device. The appearance and placement of these features may vary.
NEW AMAZON AI SEARCH TURNS WORDS INTO SHOPPABLE IMAGES
Not necessarily. Google says Universal Cart can organize products across retailers, but that doesn't mean every online store supports every feature. The products you can save depend on supported shopping experiences. Meanwhile, checkout options vary depending on the merchant. Some purchases can happen through Google Pay in the cart, while others require you to finish on the retailer's website. Google originally introduced Universal Cart in May with plans to bring it to Search, Gemini, YouTube and Gmail. However, its October 15 launch announcement specifically confirms availability across Search and Gemini in the U.S. Google has not announced a confirmed launch date for Universal Cart integration with Gmail or YouTube.
Behind the scenes, Google uses something called the Universal Commerce Protocol, or UCP. It's a shared technical standard designed to help AI-powered shopping tools communicate with retailers and payment systems. For shoppers, the technical details are less important than what they make possible. UCP helps Google connect product discovery with checkout, reducing the need to jump between different shopping experiences. Google has also been expanding AI shopping beyond the cart. Its Let Google Call feature, for example, can use AI to contact nearby stores and check product availability. Amazon has been developing AI-powered shopping tools, while OpenAI offers AI agents that can assist with shopping-related tasks. The competition to become your digital shopping assistant is heating up.
Having Google organize your shopping could be convenient, especially if you already use Search and Gemini. Still, it's worth considering how much shopping information you're comfortable keeping within your Google account. Universal Cart uses Google Wallet to help identify supported payment benefits and relevant offers. However, Google's launch announcement doesn't provide detailed information about how long Universal Cart shopping data is retained or exactly how it may be used for advertising. Before relying on the feature, review your Google account's privacy settings and Google's published privacy policies. For now, I would avoid assuming that adding something to Universal Cart keeps that shopping interest private. And if you're buying a surprise gift for someone who shares access to your Google account, think twice before saving it there. Of course, the usual online shopping precautions still apply. Before completing a purchase, check the final price and verify that you're buying from a legitimate seller. A familiar checkout experience shouldn't replace those basic habits. For more help spotting suspicious sellers, see our guide on how to tell whether an online store is real or a scam.
I like the idea of having one place to keep track of everything I'm considering buying, especially when the holidays roll around. The price alerts could be genuinely helpful. And if Google's AI can find a discount code I would have otherwise missed, I'm all for it. But I'm also watching where this is heading. Google is making shopping increasingly convenient, and that convenience can be a double-edged sword. When a company knows what you're interested in buying and makes checkout easier, there's less time to reconsider a purchase. My advice? Use Universal Cart to do your homework and save money. Just don't let the technology do the deciding for you.
Would you trust Google's AI to help you shop and choose how to pay, or are we giving tech companies too much influence over what we buy? Let us know by writing to us at CyberGuy.com.
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An uncanny strength of the second Trump administration has been its ability to be involved in so many scandals that no single one seems to become a dominant story.
Take the most recent allegations about Alina Habba, Trump's former personal defense attorney, who recently landed a plush gig working for Julio Herrera Velutini, a Venezuelan banker. Habba will get $50 million over five years to do unspecified work for a company that barely exists, according to The New York Times, while Herrera got a presidential pardon for a 2025 campaign finance charge.
That's just a typical day for the current White House, where the mingling of personal and public business has become routine. Some days, the story is President Donald Trump trying to help himself to taxpayer funds by suing the government he runs, or shipping billions of taxpayer dollars to a foreign mining company partially owned by his sons. Other times, it is Trump selling political influence in the form of digital coins, or his appointees getting caught in naked pay-to-play schemes. If you have a hard time keeping track of it all, I get it. The corruption is so deep and wide that focusing on any singular item becomes difficult.
But that constellation of corruption might finally be breaking through to voters ahead of next month's midterm elections.
A recent Fox News poll found that "government corruption" was the top issue for voters, ranking ahead of inflation and gas prices. Conservative commentators are taking notice.
"What they're saying is, 'Look, we're tired of you getting rich and us getting poor,'" former White House Chief of Staff Mick Mulvaney said this week.
Tim Carney, senior columnist at the conservative Washington Examiner, also tabs the corruption issue—along with other "avoidable mistakes" such as the Iran War and tariffs—as one of the major reasons why Democrats are likely to win the midterms:
Trump and his family have enriched themselves in this second term in ways more similar to third-world regimes or Cook County than to any previous administration. He and his family operate a financial company that has received heavy investments from Qatar's government. He's sold access to himself by selling otherwise worthless cryptocurrency. The IRS he controls settled a lawsuit with him, promising to pay him $1.8 billion (this settlement was voided by a judge).
Trump is not directly on the ballot next month, of course. And most voters might not be able to tell you the details of any single Trump scandal in detail. Even so, this may turn out to be the defining narrative of the second Trump administration, and there seems to be a growing consensus that Republicans have allowed (if not aided and abetted) his corrupt behavior, so it's time to give Democrats a shot at reining it in.
The Trump corruption issue is like the Biden cognitive decline issue in one key sense: Everyone around the president or even supporting him professionally from afar should be asked about it, and their lies/claims of ignorance should be hung around their necks like dumbbells.
— Matt Welch (@MattWelch) October 20, 2026
Vice President J.D. Vance told journalist Mark Halperin this week that he's "never seen any evidence that anybody's selling access to the president." When Halperin pushed back, Vance doubled down: "What I would say is I don't think there's evidence that the Trump family has become enriched by politics," the vice president said.
So either Vance isn't paying attention, or he's deliberately misleading. "Credit to Vance, it's as good an argument as is available to him," writes Daniel Foster at National Review. "The bad news is it's still not very good."
The internet nearly crashed on Wednesday as digital security and website administrators scrambled to patch two vulnerabilities in the PHP programming language that serves as the basis for many websites.
"Since its development in the 1990s, PHP has evolved into an essential scripting language for web development and is used across vast swaths of the internet in websites and software," explains Wired. "Everything from publishing systems like WordPress and Drupal to e-commerce platforms like Adobe's Magento are built on PHP."
Amid fears that hackers and AI agents could exploit the security weakness, many websites were taken offline. The National Security Agency and its counterparts in the United Kingdom and the European Union sounded the alarm. Even the prime minister of Japan, Sanae Takaichi, was telling website administrators to take the issue seriously.
The potential hacking abilities of advanced AI agents make these sorts of security risks more serious. In this case, however, the problem was also identified with the help of AI.
"Ryan Austin, a researcher at Calif, uncovered the flaws with help from GPT-5.6 Sol, one of OpenAI's most advanced models, during an audit of PHP's source code in August," The Wall Street Journal reports. Another security researcher had flagged the issue years ago, but it had never been fixed because it was considered "considered too difficult to exploit" by human hackers.
This is the future of humanity's digital landscape. "Given the severity of these flaws and PHP's widespread use, we consider this one of the most impactful security issues in recent memory," OpenAI said in a statement on Wednesday. "It highlights how AI can uncover security flaws with internet-scale impact, but the same capabilities can also help attackers rapidly develop offensive tools and exploits."
(A shoutout to Reason's web development team for keeping us up and running, today and every day.)
"Fanciful fiction." Media outlets also continue to face decidedly nondigital threats over articles and polls that make the president unhappy.
The White House threatened Politico on Wednesday with unspecified "consequences" for publishing "fanciful fiction" in a series of articles earlier this month about White House Chief of Staff Susie Wiles. If the articles are not retracted, it would trigger "an immediate review of Politico's relationship with the White House, and, of course, consideration of all other appropriate and available legal remedies," wrote White House counsel William O. Scharf in a letter to the media outlet's publisher.
Meanwhile, FCC Chairman Brendan Carr issued vague threats to broadcasters who cover what Carr called "Fake Polls" intended to "alter the normal patterns of voter turnout and enthusiasm."
These sorts of threats are an affront to the First Amendment, of course. But they are downstream of a more significant issue: the very existence of the FCC.
It's a problem, obviously, that the FCC is run by an authoritarian jackass. But the bigger problem is that the agency contains so many tempting tools for an authoritarian jackass to wield. https://t.co/Q4IJXntkOy
— Jesse Walker (@notjessewalker) October 21, 2026
A group dispatched by Hegseth's team in February attempted to move the historic globe, said to be used by Eisenhower during World War II.
They lifted it from its home in an Army office in the Pentagon … and dropped it. pic.twitter.com/vTjWdYXn0k
— Dan Lamothe (@DanLamothe) October 22, 2026
The post The Swamp King appeared first on Reason Magazine.
Leave it to Arundhati Roy to deliver a scorching, dizzying essay on the perils of artificial intelligence that references Greek mythology, Francis Ford Coppola, the Bible, India’s industrial history, and Tie Me Up! Tie Me Down! Plus, Emily Dickinson features in the lede:
The auguries are raining down hard. Think or Sink. Comply or Die. Look Up or be Left Out. And so, with these not-so-gentle threats, it has come to pass that the Age of AI—Actual Idiocy, Actual Super Idiocy, Recursive Snowballing-Idiocy—is upon us. Heck, I’ve already used two dashes in this opening paragraph. That, as they say, is a tell. So, perhaps I haven’t written this essay at all. You’d have to use an AI app to check if it’s actually AI, and whether I’m really, or not really, or only partially me. You can no longer use your instincts. You have to use the App. Now that AI owns the em dash, what will future generations make of Emily Dickinson and her love of them? Has she been fed to the machine, too? Will they love her less? Are we being gradually locked out of language? Does it matter anymore?
© Geert Vanden Wijngaert/Associated Press
© Bizuayehu Tesfaye/Las Vegas Review-Journal/Tribune News Service, via Getty Images
Ukraine’s military intelligence (HUR) published a 3D model and parts list of Russia’s new Filin cruise missile on 22 October. The breakdown names the Russian companies behind the missile and the foreign makers of its electronics.
HUR runs its War&Sanctions portal to trace such parts back to their makers. Its stated aim is to “deprive the aggressors of the ability to produce weapons for terror,” the portal says. Meanwhile, Russia is betting on cheap, fast cruise missiles, Serhii Beskrestnov, a freelance adviser to the president on technology, told Radio NV in mid-September. Naming the Banderol, Dan-T, Dan-M, and Gerbera-5, he warned they would soon outrun Ukraine’s jet-powered interceptors, so Ukraine needed its own cheap missiles to shoot them down.
JSC NPO Molniya, part of Russia’s Tactical Missiles Corporation, builds the Filin, HUR said. The agency called it part of a Russian defense-industry trend toward cheap jet-powered, ground-launched air-attack weapons. Russia began firing it at Ukraine in late summer 2026.
HUR’s data puts the carbon and fiberglass fuselage at 3.5 m, with a 3 m wingspan. Some parts are 3D-printed. Russia claims a top speed of 800 km/h. The range is 600–1,200 km, and the missile flies at ultra-low altitude or up to 6 km. Versions carry 50-kg or 100-kg warheads. A solid-fuel booster fires it from a ground launcher.
PLAZ LLC makes the onboard equipment, HUR said. The firm also helps produce the Garpiya, a version of Russia’s Shahed-type Geran-2 drone. Filin and Garpiya units share a similar layout and markings. Guidance combines a Chinese-made inertial navigation system with a 16-channel Kometa anti-jamming module from Russia’s VNIIR-Progress.
The electronics resemble those in other Russian missiles and drones but carry a larger share of Chinese parts. Of 81 components, 35 are American and 22 Chinese. The engine, however, is Russian: an R500 turbojet from Reynolds LLC. A similar engine earlier turned up in the S-71K Kover aviation cruise missile and S-71M Monokhrom, HUR said.
For comparison, Ukraine found more than 20 foreign components in a different cheap missile, the Banderol, in May 2025. They included 10 US microchips, and the Banderol flies on a Chinese jet engine.
© The New York Times
As of October, Russia has up to 700 ballistic and several thousand cruise missiles in reserve, and its 2026 state order for Geran-type drones and decoys such as the Gerbera exceeded 100,000 units, Ukraine’s military intelligence (HUR) told NV in figures the outlet published on 20 October. The missile stocks are roughly the same as HUR reported to NV in July, the outlet found.
Ukraine enters the heating season facing what it says is a Russian plan to hit 60 infrastructure sites this winter. HUR’s figures suggest Russia has the weapons for it, even after its fall mass strikes. In June, HUR said Russia could fire up to 100 ballistic missiles a month while keeping its stocks steady. Its drone output, meanwhile, is shifting to jets that are harder to shoot down.
Russia can make more than 200 missiles a month, 110 of them ballistic, HUR said. About 115 of its ballistic missiles are Iskander-Ms, with production of up to 65 a month. A modernized Iskander with a projected range of 550 to 700 km is in development.
At the same time, Russia holds up to 400 S-300PM and S-400 air defense missiles adapted to strike ground targets, and makes about 40 a month. Meanwhile, Kinzhal production has been temporarily paused over poor accuracy, and the capacity has gone to conventional ballistic missiles.
Russia plans to make more than 80 Kh-101 cruise missiles a month and is exceeding that, though defects in releasing them from aircraft have sent some batches back to the factories.
Russia has more than 450 Kalibrs and makes about 29 a month. Because Ukrainian air defense downs them effectively, Russia sends most new ones to its strategic reserve and to equip its fleets, HUR said. It also holds more than 600 Oniks anti-ship missiles, upgraded for ground strikes, and more than 120 Zircons.
Russia holds a reserve of about 6,200 Gerans and makes about 10,000 drones a month. Its main production hub is the Alabuga special economic zone in Tatarstan.
Since summer, Russia has shifted toward turbojet drones. “The reason is the saturation of Ukraine’s Air Force with mobile fire groups that shoot down low-speed targets en masse,” HUR said. Russia now assembles about 4,000 jet drones a month, mostly Geran-4s and Geran-5s, which fly at 400 to 500 km/h. It also makes about 2,000 cheaper propeller-driven Geran-2s, which HUR said are used to wear down air defense and locate air defense positions.
Samuel Boivin/NurPhoto via Getty Images
Hugging Face is releasing an AI model that could make it easier for scientists to study DNA and develop new genetic treatments, the company announced Thursday.
Carbon-X is a "first of its kind" model that combines DNA analysis and generation with plain language, allowing researchers to ask questions and essentially "chat with DNA," according to Lewis Tunstall, a senior research scientist at Hugging Face.
Hugging Face, which Nvidia agreed to acquire for nearly $13 billion in September, is a platform for sharing and developing AI models and also releases its own. The company worked with research labs in Italy and China on Carbon-X, which is an open-source model. Hugging Face built Carbon-X by training an existing language model, Qwen3-14B, on genomic sequences and natural language. It was trained on DNA sequences from humans, other mammals, plants, and fungi.
As an example of how Carbon-X can be used, Tunstall said a researcher could provide a DNA sequence and ask whether a particular mutation could increase a person's risk of disease. The model would then offer a prediction and explanation. It can also generate new DNA sequences, which could help researchers develop new gene therapies.
Tunstall said the company was partly motivated to build Carbon-X to prevent biology researchers from becoming dependent on the major AI labs, noting how AI has disrupted mathematics.
"If you want to really push the frontiers of mathematics, you likely have to be at one of these AI labs like OpenAI or Anthropic, because they're the ones who have the best mathematics models," he said, suggesting a similar situation is likely to play out in other fields of science.
"We wanted to provide the open research community with tools that don't make them fully dependent on some external single provider," he added.
Researchers can run Carbon-X on their own computers, avoiding the need to share sensitive patient data with external AI companies. He also said that some of the misalignment behavior observed in larger models, such as the OpenAI agents that famously hacked Hugging Face in July, has not yet been observed in smaller, more specialized models.
Tunstall said generalist chatbots also sometimes refuse to answer legitimate biology questions from researchers because they mistake them for attempts to "design a bioweapon." He said viruses were explicitly excluded from Carbon-X's training data in order to avoid misuse of the model.
While Carbon-X is likely to be used by researchers, Tunstall said the model represents a small step toward a future where AI can help provide more personalized medical care.
"I think the holy grail is, in general, this concept of personalized medicine where we're able to, as individuals, take our own patient records, our own genomes, and use this to ultimately find or even maybe design our own treatments," he said.
© Illustration by Andrei Cojocaru; photos by Getty Images
MaCabe Brown / Courier & Press / USA TODAY NETWORK via Imagn Images/Reuters
The AI industry has a problem with bragging.
Companies are announcing enormous new data centers to power the AI boom. Some promise facilities bigger than anything the industry has built before.
There's just one problem: Most of these projects may never happen.
Bernstein Research analyzed thousands of planned US data centers and concluded that only about 35% of the announced capacity is likely to get built. That's roughly 170 gigawatts of data center capacity out of a total of almost 500 gigawatts.
The rest? A significant chunk of it belongs to a category the industry has a wonderfully dismissive name for: "Bragawatts." These are ambitious announcements, often from newcomers with little experience building data centers, that have a slim chance of becoming reality.
"Press releases are cheap…concrete is not," Bernstein analysts wrote in a research note.
Bernstein began its analysis with more than 7,000 data center projects across North America, drawing on information from Aterio, a company that tracks construction through satellite imagery, permits, and other records. The analysts narrowed that to more than 5,000 projects (partly by excluding those already canceled).
Then they assessed the chances of these remaining projects being completed. The analysts considered factors such as whether construction had started, whether electricity was available, and whether the companies involved had successfully built data centers before.
The results revealed a striking divide.
Daniel Delgado Jr./Disney via Getty Images
Experienced operators including Amazon, Google, Microsoft, and Meta landed at the top. Bernstein gave these companies perfect scores of 5 out of 5 for their development credentials. Other data center specialists, such as Digital Realty, Equinix, and CoreSite, got top marks, too.
O'Leary Digital, associated with celebrity investor Kevin O'Leary, ended up at the bottom, with a credibility score of 0.35 out of 5, according to Bernstein. His company has announced 15 gigawatts of data center projects, and Bernstein estimates that only 489 megawatts, or about 3%, will actually materialize.
"Sorry, Kevin," the analysts wrote.
Although the term "bragawatts" has been doing the rounds in the data center industry lately, it's unclear who coined it, Bernstein analyst Madison Rezaei told me.
"I wish I could take credit for that," she said. "I believe I originally heard it from an Equinix executive, but I don't think he owned it either."
She said that while some ambitious newcomers could succeed, they haven't yet demonstrated they can deliver.
"It's not that all of these guys are sort of terrible and not going to deliver, but we just have lower confidence because we don't know them," Rezaei said.
O'Leary Digital disputed Bernstein's assessment, saying the research doesn't account for substantial work that occurs before construction begins.
While acknowledging that O'Leary Digital is a young company, CEO Paul Palandjian said the team has decades of experience building major infrastructure projects and that its proposed 15 gigawatts of capacity would be built in stages over several years.
The company said it has secured binding agreements covering about 11,000 acres in Utah and 13,000 acres in Alberta, obtained a 30-year development agreement in Utah, and made progress on planning, engineering, and permits at both sites. It also said the projects would generate their own electricity.
The company said its early development work is funded, additional capital is committed to reaching key milestones, and experienced engineering and construction partners are involved.
"We would rather be judged on milestones than on a model," Palandjian said.
USA TODAY Network via Reuters Connect
Other low scorers in the "bragawatt" brigade included Vermaland and Joule Capital Partners, according to Bernstein analysis based on Aterio data.
Joule has announced 50 data center projects with a combined capacity of 11.7 gigawatts. Bernstein estimates that only about 11% of that capacity will actually get built. Almost all of Joule's planned capacity remains at the announcement stage, with little evidence of construction progress or of major customers committing to use the facilities, Bernstein wrote in a July note to investors.
The analysts gave Joule a credibility score of 2.05 out of 5, placing it among the lowest-ranked developers in its database.
"An announcement in search of a project," the analysts wrote.
Vermaland has announced plans for a massive data center project in Arizona. Bernstein estimates that only 4% of its proposed 2.2 gigawatts of capacity will get built. The company is primarily a landowner, not a data center developer. Its proposed $33 billion La Osa project near Eloy had already been sharply scaled back amid local opposition and without construction approval. In late August, regulators formally rejected the project. Even before that, the analysts gave Vermaland a credibility score of 0.75 out of 5.
Joule and Vermaland didn't respond to emails seeking comment this week.
Sergio Toro, CEO of Aterio, sees similar patterns in his firm's voluminous, detailed data.
Aterio's tracking shows that roughly 30 to 40 gigawatts of new data center capacity get announced each month. Yet only about 7 gigawatts begin construction each month, while 2 to 3 gigawatts actually start operating.
This leaves a yawning gap.
Many announced projects get withdrawn before construction begins — and before real money has been spent.
"They just make the announcement, but they didn't get their approvals. Or they make multiple filings in multiple locations to see which one gets selected," Toro told me. "That's why we track with satellite if there's real movement on the ground or not."
Indeed, Bernstein analysts wrote recently that the amount of "stranded" data center capacity has surged. These are projects that are either canceled, delayed, or not approved.
Toro sees three broad groups competing to build AI infrastructure.
At the top are the established technology giants, including Amazon, Microsoft, and Google. They've built data centers for decades and generally deliver on their commitments. Most of their projects will get done, he said.
In the middle are "neoclouds," newer companies such as CoreWeave that rent out computing power specifically for AI. Although they're more vulnerable to financing problems and delays, many are making solid progress, especially because some of these players already have access to electricity.
"We see them advancing quite well," Toro said. "Sometimes we see some delays, but it's not something significant or any kind of big capacity that is at risk."
Then come the newcomers making extraordinary promises. That's where most delays and cancellations happen, Toro said.
Noah Berger/Getty Images via Amazon Web Services
Not every project that disappears was a fantasy, though. Even a top player like Amazon struggles sometimes to secure electricity and other supplies on time for these huge projects.
Business Insider's Eugene Kim reported exclusively this week on the challenges Amazon faces with its record AI buildout.
The biggest, most experienced tech companies deliberately pursue more potential data center capacity than they need because they know some developments will fail or get delayed.
Major AI companies were committing to three or four times the space and electricity they needed over the following two years, Jeffrey Moerdler, a data center lawyer, estimated during an interview with Bernstein analysts.
His reasoning: Of data center projects that haven't started construction, roughly a third will arrive on schedule, another third will be delayed, and the remainder won't happen.
Rezaei and Toro estimate that the top players don't over-commit that much — more like double the capacity they need at most.
The strategy provides a "Plan B," as Toro put it, in case of delays involving electricity, equipment, permits, local opposition, or other factors.
Brandon Bell/Getty Images
This helps explain another extraordinary number.
Data center companies have requested connections for roughly 450 gigawatts of electricity demand on Texas' main power grid, more than five times the grid's roughly 85 gigawatts of existing capacity, according to Toro and others.
Many of those requests are placeholders rather than firm construction plans. Toro calls them "ghost projects."
These speculative projects clog the waiting lists for electricity connections, making the electricity shortage look a lot worse than it actually is.
"Developers routinely spam projects across several sites, and many are speculative builds with no customer yet," Ryan McEntush, a partner at venture capital firm Andreessen Horowitz, wrote in a recent blog. "Often these new developers have never even plugged in a GPU, let alone a power plant."
Texas has paused applications to review and weed out projects that aren't serious. Toro, from Aterio, expects this to favor the established players at the expense of the bragawatts.
None of this means the AI infrastructure boom is imaginary.
Aterio tracks thousands of buildings, including major projects already under construction. Bernstein estimates that nearly 80% of the capacity the largest technology companies are directly developing is credible.
And when speculative projects disappear, Rezaei doesn't expect a wave of unpaid debt. Many will fail before building begins, the stage when developers borrow serious money through project financing.
Some of those missing data centers were never really coming in the first place.
Sign up for the AI Insider newsletter here. Reach out to me via email at abarr@businessinsider.com
© Annegret Hilse/Reuters
For two decades, data centers were relatively safe, lucrative real estate investments. They attracted investors because they served as digital infrastructure — the essential plumbing that keeps the internet running. The growth of artificial intelligence (AI) and its increased demands on computing power has meant data centre builders are in a race to build out […]
The post Australia’s NextDC stock collapse fires a global AI warning appeared first on Asia Times.
The Council of the European Union adopted its negotiating position on Wednesday, 21st October, clearing the way for negotiations with the European Parliament once MEPs establish their position.
The measures form part of the European Commission’s Digital Omnibus package, introduced in November 2025, and represent one of Brussels’ most substantial attempts to simplify the regulatory obligations imposed on businesses operating across the single market.
The proposed reforms would modify several provisions of the GDPR, which has governed the processing of personal data across the EU since May 2018.
Rather than replacing the legislation, the Council wants to clarify existing obligations, particularly those concerning pseudonymised information, requests for access to personal data and the use of information in scientific research.
The agreed position retains the existing definition of personal data while introducing provisions intended to clarify when pseudonymised information can be linked to an identifiable individual.
Companies would also benefit from simplified procedures for handling manifestly unfounded or excessive data requests and from reduced information requirements in certain low-risk circumstances.
Another proposed change would extend the deadline for notifying authorities of personal data breaches, while establishing more consistent reporting templates across the EU.
For multinational companies, which currently navigate different interpretations of data protection obligations by national authorities, these provisions could reduce compliance costs and administrative duplication.
However, the changes have raised concerns among European privacy regulators.
In a joint opinion published in February, the European Data Protection Board and European Data Protection Supervisor warned that parts of the Commission’s original proposal could create legal uncertainty and undermine existing protections.
They were particularly concerned about proposals affecting the definition of personal data and the Commission’s potential role in determining when pseudonymised information falls outside GDPR requirements.
The Council’s decision to retain the existing definition addresses part of that debate, although the final legislative text remains subject to negotiations.
One of the most visible changes would affect the consent notices encountered by Europeans when visiting websites.
Under the Council’s proposal, additional categories of cookies and similar tracking technologies could be used without obtaining explicit consent, provided the relevant legal conditions are satisfied.
The proposed exemptions include technologies necessary to deliver a service, maintain device security or conduct audience measurement.
For website operators, publishers and online businesses, the changes could reduce the number of consent requests displayed to visitors and simplify technical compliance.
The current system has generated extensive legal disputes over whether consent is genuinely voluntary and whether tracking technologies collect information beyond what users have authorised.
EU Today has previously examined the enforcement of these obligations, including a Belgian court ruling concerning the legality of the advertising industry’s consent framework.
The latest proposal would not abolish consent requirements for commercial tracking or behavioural advertising. Technologies falling outside the permitted exemptions would remain subject to the applicable privacy rules.
The package also addresses the growing number of reporting obligations imposed on European businesses under overlapping cybersecurity legislation.
The Commission originally proposed a single European reporting mechanism for certain data and cybersecurity incidents.
Member states have instead agreed to establish national entry points, supported by an EU-level information system and provisions for coordinating cross-border notifications.
The Council’s position would also clarify the legal grounds for certain uses of personal data in artificial intelligence systems and introduce safeguards for processing sensitive information in specified circumstances.
These provisions follow increasingly complicated disputes over the application of European privacy legislation to AI development and automated decision-making.
As EU Today reported in its coverage of a major GDPR enforcement case involving Uber, automated processing already presents substantial compliance risks for companies operating within the bloc.
The Commission estimates that its wider digital simplification initiative could save European businesses up to €5 billion in administrative costs by 2029.
The initiative reflects pressure from European governments and business organisations to reduce the regulatory fragmentation that makes operating across multiple EU jurisdictions more expensive.
The Digital Omnibus is part of a broader legislative programme influenced by the competitiveness reports produced by former Italian prime ministers Enrico Letta and Mario Draghi.
Under the Council’s negotiating mandate, several existing data-related rules would also be consolidated, while provisions governing the protection of trade secrets would be strengthened.
The European Parliament must now determine its negotiating position before formal discussions between the institutions can begin. Until the legislation is agreed and adopted, existing GDPR, cookie consent and cybersecurity requirements remain in force.
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Even Google's CEO needs help keeping up with Google.
On the Sources podcast released Wednesday, Sundar Pichai described to host Alex Heath how he delegates some of the information-gathering that comes with running the tech giant.
“It could easily take me an hour a day to kind of catch up, what's happened in the last 24 hours, right?" Pichai said. "But now I have agents running which summarize and bring that information to me. I can still go deeper, and I do so often."
Pichai said that his AI agents give him a way to "understand the model development arc," figure out how Google's computing resources are being used, and follow threads spread across numerous internal chat groups without having to read through every conversation himself.
“Similarly, there are agents with telemetry into our compute usage by product area, efficiency, utilization, and giving me inputs and insights, you know," Pichai added. "I think it's made all of us, you know, be better at what we do."
That doesn't mean Pichai has handed over the important calls to AI. He said humans — including himself — remain directly involved in consequential decisions about allocating computing resources.
Managing agents is becoming a skill in its own right, giving some workers a new set of headaches, from checking the bots' output to preventing them from duplicating work or straying beyond their assignments. Business Insider previously reported that the need to manage agents is making everyone a boss without higher pay.
Delegating to bots doesn't necessarily make work easier, either. A Cisco engineering director who manages more than 10 agents told Business Insider that overseeing them involves more task switching and can make work feel more intense without shortening his days.
For the Google CEO, however, continuous work is a plus.
"So because your agents, they're running in the cloud, they're running 24/7, they have your context, and so they can pick up things where you left off," Pichai said. "It's a continuum there. By the time it's doing that, you would be applying yourself to the next problem and so on."
© Victor Llorente for The New York Times
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