Technology

Commodore’s Callback 8020 is a phone “where the customer is not the product.”

Late last month, I began to consider withdrawing some money from my savings account to buy gold. It’s the first time I’ve ever thought about panic-buying. For all of the firewalls and two-factor-authentication codes, the safety of the internet is starting to falter. Hackers are gaining the upper hand over organizations around the world—hospitals, energy grids, government agencies, and, yes, banks.

As AI tools have become extremely good at writing code, they’ve also become extremely good at pulling off cyberattacks. (Malware, after all, is still software.) The result has been a change in the scale, speed, and sophistication of hacks that is difficult to overstate: Among its tens of thousands of clients, the cybersecurity firm Palo Alto Networks identified a fourfold increase in daily attacks from 2024 to 2025. Hackers are developing AI-enhanced computer viruses that adapt on the fly to avoid detection. They are automating cyber-espionage campaigns on foreign governments. They are stealing data in minutes instead of hours. “There’s a crazy amount of offensive activity happening right now,” Alex Stamos, a former chief security officer of Yahoo and Facebook, told me. “Companies are getting hacked every single day.”

Last week, we talked about one huge question, “How the hell are you supposed to have a career in tech in 2026?” That’s pretty specific to this current moment, but there are some timeless, more perennial questions I've been sharing with friends for years that I wanted to give to all of you. They're a short list of questions that help you judge whether a job that you’re considering is going to crush your soul or not.

Obviously, not everyone is going to get to work in an environment that has perfect answers to all of these questions; a lot of the time, we’re lucky just to get a place to work at all. But these questions are framed in this way to encourage us all to aspire towards roles that enable us to do our best work, to have the biggest impact, and to live according to our values.

Don't count your bit barns before they've at least started to hatch. Developers continue to announce new datacenter construction projects, but construction work for many due to come online this year or next appear not to have commenced, while planned capacity may have been overestimated.

According to financial analyst Jefferies, known promises to build new stateside datacenters suggest 160 GW worth of infrastructure will be operational in the country by 2032

In a research note shared with The Register, the firm reports pervasive delays and claims that only 12 GW out of 24 GW of datacenter capacity scheduled for 2026 is currently under construction. The situation is even worse for the 2027/2028 timeframe, as substantial construction of as much as 80 percent of the planned capacity does not appear to have started yet.

The reasons for the delays are familiar: zoning and/or permitting challenges, interconnection setbacks, problems accessing energy supply, labor shortages, and the signing of commercial contracts with end users.

archive.is link

A trove of internal records from a secret society for powerful figures in US politics, finance, and tech was left exposed online, WIRED has confirmed, naming participants in its events and revealing sensitive personal details they were assured would stay private.

The group, called Dialog, is a private, invitation-only organization cofounded in 2006 by the billionaire tech investor Peter Thiel. It convenes US officials, foreign government figures, and Silicon Valley executives at off-the-record annual retreats. Dialog has spent two decades declining to disclose its members.

A directory in the website's code was first revealed by the Swiss hacktivist maia arson crimew. Known for exposing the US government’s No Fly List and breaching the surveillance-camera company Verkada, crimew tells WIRED the directory surfaced via an anonymous tip. WIRED independently verified its contents.

Today, I can exclusively report, based on audited financial documents viewed by this publication that have been independently verified by the Financial Times, that OpenAI lost around $38.5 billion in 2025, as well as other crucial details about the financial condition of the company.

Due to the seriousness of this story, I am not going to do very much editorializing, as the numbers speak for themselves.

It's bullet points from here to the conclusion. Dry stuff, but important data as these idiots persevere in finding even larger idiots to give them money via IPO.

Fox Corp is buying Roku in a cash-and-stock deal ⁠valued at about $22bn in a bet that pairing its sports and news programming with a top TV streaming platform will strengthen its position as audiences shift online.

The deal, ⁠announced on Monday, gives ⁠Fox access to ​the more than 100m households using Roku’s streaming platform, potentially helping the cable TV-reliant media company better target ads and reduce reliance on traditional distribution.

One of the first companies to bring streaming ‌platforms like Netflix and YouTube to television through connected devices and smart TVs, Roku’s business is largely driven by advertising and subscription revenue from streaming apps on its platform. The company also operates the free-to-watch Roku Channel.

Advertising is its largest component, with revenue of $613m in the first quarter, up 27% year-on-year.

Soon, you'll be able to use your Roku to support Fox News!

Age and ID verification also coming to LLMs. It's horrible.

It's clear that communities now have an effective playbook to block data center construction. This week, researchers flagged the first quarter of 2026 as producing the "most blocked and delayed data center projects on record," NBC News reported.

Data Center Watch, a project from AI intelligence firm 10a Labs that tracks data center fights around the US, reported that protestors "blocked or delayed at least 75 projects nationwide worth about $130 billion from January through March," NBC News reported

That's "the most in a three-month period since the group began tracking in 2023," and it shouldn't be parsed as "a cyclical spike," the researchers said. Instead, there's been a "structural shift," as "communities have internalized an opposition playbook, legislative sessions introduced formal regulatory uncertainty, and the number of active opposition groups more than doubled to 833 across 49 states," researchers said.

The political momentum behind data center protests is expected to influence the upcoming midterm elections, with both parties increasingly sympathizing with resistance as opposition intensifies.

Artificial Intelligence detects diseases before symptoms appear—discover early warning signs and get faster care with smarter diagnosis today.

If you hang out in any even vaguely AI-skeptical parts of the Internet, you’ve probably stumbled on plenty of memes and posts premised on data centers’ insatiable thirst for water to power evaporative cooling. But a new report from Amazon highlights just how little water all these AI data centers are using in aggregate, on a relative basis, even as individual data centers can strain local water supplies.

In a Thursday blog post, Amazon claims its data centers withdrew “about 2.5 billion gallons” globally in 2025. That number sounds incredibly large at first glance, but it looks downright puny compared to the 117 trillion gallons of water withdrawn in the US alone in 2015. It’s also useful to compare Amazon’s number to stats from more water-intensive areas, from the 3.3 trillion gallons used annually on US lawns and landscaping to the 1.3 trillion gallons a year used in California almond orchards to the 531 billion gallons a year used just for US golf courses.

Amazon is just one company, of course, and a relative latecomer to reporting its data center water usage numbers. Google data centers withdrew about more than 6.1 billion gallons of water in 2024, on top of about 2.75 billion gallons from Microsoft and about 1.4 billion gallons from Meta in the same year.

All told, a 2021 Nature study estimates that all US data centers combined consumed about 163 billion gallons of water that year, a number that includes “indirect” consumption from non-renewable power sources. That number has doubtlessly increased in the AI-driven years since that study was published—one analysis estimates that Texas data centers alone used 25 to 49 billion gallons in 2024, and could grow to withdraw 399 billion gallons in 2030. But even annual data center water usage measured in the trillions would represent a figurative (and kind of literal) drop in the bucket compared to national and worldwide water usage statistics.

As AI companies get ready to go public and we get a deeper look at their inner workings, it’s only natural to have questions about their finances, like “Do they make money?” and “How?” Here are a few examples to help the average layperson understand the business side of AI.

According to Shopify, the best e-commerce platform is Shopify. On its blog, the company has published at least 60 different ranked listicles, including “10 Best Ecommerce Platforms for Small Business in 2026,” “11 Best Ecommerce Platforms for Your Business in 2026,” “The 11 Best Cheap Ecommerce Platforms for Small Business (2026),” and “Best Ecommerce Software 2026: Compare 11 Top Platforms.” The competitors that come in second and beyond vary, but the No. 1 pick is always Shopify.

If rankings produced by the very company at the top of the list seem unlikely to fool anyone, that’s because humans probably aren’t the target audience. Chatbots are. When I recently asked ChatGPT for the “best way to set up an online storefront,” the AI tool identified Shopify as the first option. It wasn’t immediately clear how ChatGPT arrived at that recommendation, but a list of citations that accompanied the answer yielded a clue: Shopify’s own rankings.

For the quarter century that Google has been the de facto front door to the web, businesses have tried to find ways to get their pages at the top of search results. You’ve surely felt the influence of search-engine optimization, even if you don’t know the term. When you search for a recipe and have to scroll past the author’s rambling reminiscences about their great-aunt’s kitchen, that’s a form of SEO at work. Years ago, it became conventional wisdom among recipe bloggers that Google’s search rankings favored longer, more distinctive articles. (Some of them also just liked to spin a yarn.)

Now chatbots are cannibalizing the traditional search engine. More people are asking questions directly of AI tools such as ChatGPT and Claude. And searching Google now often yields an AI response, shunting the site’s famous “10 blue links” to the bottom of the results page. Last month, Google announced what it billed as the biggest change to search in 25 years: The search box now automatically expands as you type, and sometimes morphs into a chatbot. As a result, the SEO industry is scurrying to figure out how to get search bots to recommend a given product—a practice sometimes called “GEO,” for generative-engine optimization. To put it more bluntly, your search results are getting sloptimized.

https://archive.is/HqNes

it's funny

No matter how much you dress up whatever AI service has gaslit you into believing it’s sentient, generative AI is inherently limited, impossibly expensive and economically unviable. Its services cost too much to run, its progenitors have no path to profitability, and no amount of rigged benchmarks and anecdotal examples of theoretical engineering teams that are “10x’d” can make up for the fact that you can’t measure the cost of an LLM-driven task or its return on investment.

Anyone claiming that you have to “measure AI’s ROI differently” is attempting to con either you or themselves. While it’s tough to measure the ROI of a particular worker or project, most workers and projects don’t increase your operating expenses by anywhere from 10% to 100% under the vaguest of promises that you might be “doing the future.” AI is calamitously expensive and, despite years of promises of it getting cheaper for both those running AI services and its customers, costs have only ever increased.

I think that’s by design. AI labs want their costs to be high so that they can continue growing at ridiculous rates, all so that they can keep feeding money to their hyperscaler compute partners who then invest that money right back into them, creating further reasons to keep buying NVIDIA GPUs, so that NVIDIA can then invest that money back into either AI compute providers (who OpenAI and Anthropic pay) or the AI labs themselves.

Concepts like “efficiency” or “cost reduction” run counter to the greater narrative of AI’s voracious sprawl of data center capex and still-theoretical AI revenue. If OpenAI or Anthropic were to seek profitability or sustainability (assuming these things were possible), that would create less demand for AI compute, which would mean less demand for Azure or Google Cloud or Amazon Web Services or CoreWeave or Oracle Cloud Infrastructure, which would in turn mean less demand for NVIDIA GPUs.

The problem with this marvelous plan is that at some point there had to be an honest transaction — real, honest, sustainable demand based on a reliable product that people liked paying for because they understood its value. Right now, AI revenues are either chaotically experimental or so thoroughly-subsidized that labs are giving away hundreds of dollars a user in the hopes that at some point said user might want to pay even more money for measurably less value, the kind of proposition you make when you think your customers are fucking idiots.