Paul Patrick – Page 2

Vision Pro M5 review: It’s time for Apple to make some tough choices

AI, Apple, Apple M5, apple vision pro, ar, augmented reality, Features, metaverse, Mixed Reality, spatial computing, Tech, virtual reality, vision pro, visionOS, visionos 26, vr, XR / Paul Patrick / November 26, 2025

A state of the union from someone who actually sort of uses the thing.

The M5 Vision Pro with the Dual Knit Band. Credit: Samuel Axon

With the recent releases of visionOS 26 and newly refreshed Vision Pro hardware, it’s an ideal time to check in on Apple’s Vision Pro headset—a device I was simultaneously amazed and disappointed by when it launched in early 2024.

I still like the Vision Pro, but I can tell it’s hanging on by a thread. Content is light, developer support is tepid, and while Apple has taken action to improve both, it’s not enough, and I’m concerned it might be too late.

When I got a Vision Pro, I used it a lot: I watched movies on planes and in hotel rooms, I walked around my house placing application windows and testing out weird new ways of working. I tried all the neat games and educational apps, and I watched all the immersive videos I could get ahold of. I even tried my hand at developing my own applications for it.

As the months went on, though, I used it less and less. The novelty wore off, and as cool as it remained, practicality beat coolness. By the time Apple sent me the newer model a couple of weeks ago, I had only put the original one on a few times in the prior couple of months. I had mostly stopped using it at home, but I still took it on trips as an entertainment device for hotel rooms now and then.

That’s not an uncommon story. You even see it in the subreddit for Vision Pro owners, which ought to be the home of the device’s most dedicated fans. Even there, people say, “This is really cool, but I have to go out of my way to keep using it.”

Perhaps it would have been easier to bake it into my day-to-day habits if developer and content creator support had been more robust, a classic chicken-and-egg problem.

After a few weeks of using the new Vision Pro hardware refresh daily, it’s clear to me that the platform needs a bigger rethink. As a fan of the device, I’m concerned it won’t get that, because all the rumors point to Apple pouring its future resources into smart glasses, which, to me, are a completely different product category.

What changed in the new model?

For many users, the most notable change here will be something you can buy separately (albeit at great expense) for the old model: A new headband that balances the device’s weight on your head better, making it more comfortable to wear for long sessions.

Dubbed the Dual Knit Band, it comes with an ingeniously simple adjustment knob that can be used to tighten or loosen either the band that goes across the back of your head (similar to the old band) or the one that wraps around the top.

It’s well-designed, and it will probably make the Vision Pro easier to use for many people who found the old model to be too uncomfortable—even though this model is slightly heavier than its predecessor.

The band fit is adjusted with this knob. You can turn it to loosen or tighten one strap, then pull it out and turn it again to adjust the other. Credit: Samuel Axon

I’m one of the lucky few who never had any discomfort problems with the Vision Pro, but I know a bunch of folks who said the pressure the device put on their foreheads was unbearable. That’s exactly what this new band remedies, so it’s nice to see.

The M5 chip offers more than just speed

Whereas the first Vision Pro had Apple’s M2 chip—which was already a little behind the times when it launched—the new one adds the M5. It’s much faster, especially for graphics-processing and machine-learning tasks. We’ve written a lot about the M5 in our articles on other Apple products if you’re interested to learn more about it.

Functionally, this means a lot of little things are a bit faster, like launching certain applications or generating a Persona avatar. I’ll be frank: I didn’t notice any difference that significantly impacted the user experience. I’m not saying I couldn’t tell it was faster sometimes. I’m just saying it wasn’t faster in a way that’s meaningful enough to change any attitudes about the device.

It’s most noticeable with games—both native mixed-reality Vision Pro titles and the iPad versions of demanding games that you can run on a virtual display on the device. Demanding 3D games look and run nicer, in many cases. The M5 also supports more recent graphics advancements like ray tracing and mesh shading, though very few games support them, even in terms of iPad versions.

All this is to say that while I always welcome performance improvements, they are definitely not enough to convince an M2 Vision Pro owner to upgrade, and they won’t tip things over for anyone who has been on the fence about buying one of these things.

The main perk of the new chip is improved efficiency, which is the driving force behind modestly increased battery life. When I first took the M2 Vision Pro on a plane, I tried watching 2021’s Dune. I made it through the movie, but just barely; the battery ran out during the closing credits. It’s not a short movie, but there are longer ones.

Now, the new headset can easily get another 30 or 60 minutes, depending on what you’re doing, which finally puts it in “watch any movie you want” territory.

Given how short battery life was in the original version, even a modest bump like that makes a big difference. That, alongside a marginally increased field of view (about 10 percent) and a new 120 Hz maximum refresh rate for passthrough are the best things about the new hardware. These are nice-to-haves, but they’re not transformational by any means.

We already knew the Vision Pro offered excellent hardware (even if it’s overkill for most users), but the platform’s appeal is really driven by software. Unfortunately, this is where things are running behind expectations.

For content, it’s quality over quantity

When the first Vision Pro launched, I was bullish about the promise of the platform—but a lot of that was contingent on a strong content cadence and third-party developer support.

And as I’ve written since, the content cadence for the first year was a disappointment. Whereas I expected weekly episodes of Apple’s Immersive Videos in the TV app, those short videos arrived with gaps of several months. There’s an enormous wealth of great immersive content outside of Apple’s walled garden, but Apple didn’t seem interested in making that easily accessible to Vision Pro owners. Third-party apps did some of that work, but they lagged behind those on other platforms.

The first-party content cadence picked up after the first year, though. Plus, Apple introduced the Spatial Gallery, a built-in app that aggregates immersive 3D photos and the like. It’s almost TikTok-like in that it lets you scroll through short-form content that leverages what makes the device unique, and it’s exactly the sort of thing that the platform so badly needed at launch.

The Spatial Gallery is sort of like a horizontally-scrolling TikTok for 3D photos and video. Credit: Samuel Axon

The content that is there—whether in the TV app or the Spatial Gallery—is fantastic. It’s beautifully, professionally produced stuff that really leans on the hardware. For example, there is an autobiographical film focused on U2’s Bono that does some inventive things with the format that I had never seen or even imagined before.

Bono, of course, isn’t everybody’s favorite, but if you can stomach the film’s bloviating, it’s worth watching just with an eye to what a spatial video production can or should be.

I still think there’s significant room to grow, but the content situation is better than ever. It’s not enough to keep you entertained for hours a day, but it’s enough to make putting on the headset for a bit once a week or so worth it. That wasn’t there a year ago.

The software support situation is in a similar state.

App support is mostly frozen in the year 2024

Many of us have a suite of go-to apps that are foundational to our individual approaches to daily productivity. For me, primarily a macOS user, they are:

Firefox
Spark
Todoist
Obsidian
Raycast
Slack
Visual Studio Code
Claude
1Password

As you can see, I don’t use most of Apple’s built-in apps—no Safari, no Mail, no Reminders, no Passwords, no Notes… no Spotlight, even. All that may be atypical, but it has never been a problem on macOS, nor has it been on iOS for a few years now.

Impressively, almost all of these are available on visionOS—but only because it can run iPad apps as flat, virtual windows. Firefox, Spark, Todoist, Obsidian, Slack, 1Password, and even Raycast are all available as supported iPad apps, but surprisingly, Claude isn’t, even though there is a Claude app for iPads. (ChatGPT’s iPad app works, though.) VS Code isn’t available, of course, but I wasn’t expecting it to be.

Not a single one of these applications has a true visionOS app. That’s too bad, because I can think of lots of neat things spatial computing versions could do. Imagine browsing your Obsidian graph in augmented reality! Alas, I can only dream.

You can tell the native apps from the iPad ones: The iPad ones have rectangular icons nested within circles, whereas the native apps fill the whole circle. Credit: Samuel Axon

If you’re not such a huge productivity software geek like me and you use Apple’s built-in apps, things look a little better, but surprisingly, there are still a few apps that you would imagine would have really cool spatial computing features—like Apple Maps—that don’t. Maps, too, is just an iPad app.

Even if you set productivity aside and focus on entertainment, there are still frustrating gaps. Almost two years later, there is still no Netflix or YouTube app. There are decent-enough third-party options for YouTube, but you have to watch Netflix in a browser, which is lower-quality than in a native app and looks horrible on one of the Vision Pro’s big virtual screens.

To be clear, there is a modest trickle of interesting spatial app experiences coming in—most of them games, educational apps, or cool one-off ideas that are fun to check out for a few minutes.

All this is to say that nothing has really changed since February 2024. There was an influx of apps at launch that included a small number of show-stoppers (mostly educational apps), but the rest ranged from “basically the iPad app but with one or two throwaway tech-demo-style spatial features you won’t try more than once” to “basically the iPad app but a little more native-feeling” to “literally just the iPad app.” As far as support from popular, cross-platform apps, it’s mostly the same list today as it was then.

Its killer app is that it’s a killer monitor

Even though Apple hasn’t made a big leap forward in developer support, it has made big strides in making the Vision Pro a nifty companion to the Mac.

From the start, it has had a feature that lets you simply look at a Mac’s built-in display, tap your fingers, and launch a large, resizable virtual monitor. I have my own big, multi-monitor setup at home, but I have used the Vision Pro this way sometimes when traveling.

I had some complaints at the start, though. It could only do one monitor, and that monitor was limited to 60 Hz and a standard widescreen resolution. That’s better than just using a 14-inch MacBook Pro screen, but it’s a far cry from the sort of high-end setup a $3,500 price tag suggests. Furthermore, it didn’t allow you to switch audio between the two devices.

Thanks to both software and hardware updates, that has all changed. visionOS now supports three different monitor sizes: the standard widescreen aspect ratio, a wider one that resembles a standard ultra-wide monitor, and a gigantic, ultra-ultra-wide wrap-around display that I can assure you will leave no one wanting for desktop space. It looks great. Problem solved! Likewise, it will now transfer your Mac audio to the Vision Pro or its Bluetooth headphones automatically.

All of that works not just on the new Vision Pro, but also on the M2 model. The new M5 model exclusively addresses the last of my complaints: You can now achieve higher refresh rates for that virtual monitor than 60 Hz. Apple says it goes “up to 120 Hz,” but there’s no available tool for measuring exactly where it’s landing. Still, I’m happy to see any improvement here.

This is the standard width for the Mac monitor feature… Samuel Axon

Through a series of updates, Apple has turned a neat proof-of-concept feature into something that is genuinely valuable—especially for folks who like ultra-wide or multi-monitor setups but have to travel a lot (like myself) or who just don’t want to invest in the display hardware at home.

You can also play your Mac games on this monitor. I tried playing No Man’s Sky and Cyberpunk 2077 on it with a controller, and it was a fantastic experience.

This, alongside spatial video and watching movies, is the Vision Pro’s current killer app and one of the main areas where Apple has clearly put a lot of effort into improving the platform.

Stop trying to make Personas happen

Strangely, another area where Apple has invested quite a bit to make things better is in the Vision Pro’s usefulness as a communications and meetings device. Personas—the 3D avatars of yourself that you create for Zoom calls and the like—were absolutely terrible when the M2 Vision Pro came out.

There is also EyeSight, which uses your Persona to show a simulacrum of your eyes to people around you in the real world, letting them know you are aware of your surroundings and even allowing them to follow your gaze. I understand the thought behind this feature—Apple doesn’t want mixed reality to be socially isolating—but it sometimes puts your eyes in the wrong place, it’s kind of hard to see, and it honestly seems like a waste of expensive hardware.

Primarily via software updates, I’m pleased to report that Personas are drastically improved. Mine now actually looks like me, and it moves more naturally, too.

I joined a FaceTime call with Apple reps where they showed me how Personas float and emote around each other, and how we could look at the same files and assets together. It was indisputably cool and way better than before, thanks to the improved Personas.

I can’t say as much for EyeSight, which looks the same. It’s hard for me to fathom that Apple has put multiple sensors and screens on this thing to support this feature.

In my view, dropping EyeSight would be the single best thing Apple could do for this headset. Most people don’t like it, and most people don’t want it, yet there is no question that its inclusion adds a not-insignificant amount to both the price and the weight, the product’s two biggest barriers to adoption.

Likewise, Personas are theoretically cool, and it is a novel and fun experience to join a FaceTime call with people and see how it works and what you could do. But it’s just that: a novel experience. Once you’ve done it, you’ll never feel the need to do it again. I can barely imagine anyone who would rather show up to a call as a Persona than take the headset off for 30 minutes to dial in on their computer.

Much of this headset is dedicated to this idea that it can be a device that connects you with others, but maintaining that priority is simply the wrong decision. Mixed reality is isolating, and Apple is treating that like a problem to be solved, but I consider that part of its appeal.

If this headset were capable of out-in-the-world AR applications, I would not feel that way, but the Vision Pro doesn’t support any application that would involve taking it outside the home into public spaces. A lot of the cool, theoretical AR uses I can think of would involve that, but still no dice here.

The metaverse (it’s telling that this is the first time I’ve typed that word in at least a year) already exists: It’s on our phones, in Instagram and TikTok and WeChat and Fortnite. It doesn’t need to be invented, and it doesn’t need a new, clever approach to finally make it take off. It has already been invented. It’s already in orbit.

Like the iPad and the Apple Watch before it, the Vision Pro needs to stop trying to be a general-purpose device and instead needs to lean into what makes it special.

In doing so, it will become a better user experience, and it will get lighter and cheaper, too. There’s real potential there. Unfortunately, Apple may not go that route if leaks and insider reports are to be believed.

There’s still a ways to go, so hopefully this isn’t a dead end

The M5 Vision Pro was the first of four planned new releases in the product line, according to generally reliable industry analyst Ming-Chi Kuo. Next up, he predicted, would be a full Vision Pro 2 release with a redesign, and a Vision Air, a cheaper, lighter alternative. Those would all precede true smart glasses many years down the road.

I liked that plan: keep the full-featured Vision Pro for folks who want the most premium mixed reality experience possible (but maybe drop EyeSight), and launch a cheaper version to compete more directly with headsets like Meta’s Quest line of products, or the newly announced Steam Frame VR headset from Valve, along with planned competitors by Google, Samsung, and others.

True augmented reality glasses are an amazing dream, but there are serious problems of optics and user experience that we’re still a ways off from solving before those can truly replace the smartphone as Tim Cook once predicted.

All that said, it looks like that plan has been called into question. A Bloomberg report in October claimed that Apple CEO Tim Cook had told employees that the company was redirecting resources from future passthrough HMD products to accelerate work on smart glasses.

Let’s be real: It’s always going to be a once-in-a-while device, not a daily driver. For many people, that would be fine if it cost $1,000. At $3,500, it’s still a nonstarter for most consumers.

I believe there is room for this product in the marketplace. I still think it’s amazing. It’s not going to be as big as the iPhone, or probably even the iPad, but it has already found a small audience that could grow significantly if the price and weight could come down. Removing all the hardware related to Personas and EyeSight would help with that.

I hope Apple keeps working on it. When Apple released the Apple Watch, it wasn’t entirely clear what its niche would be in users’ lives. The answer (health and fitness) became crystal clear over time, and the other ambitions of the device faded away while the company began building on top of what was working best.

You see Apple doing that a little bit with the expanded Mac spatial display functionality. That can be the start of an intriguing journey. But writers have a somewhat crass phrase: “kill your darlings.” It means that you need to be clear-eyed about your work and unsentimentally cut anything that’s not working, even if you personally love it—even if it was the main thing that got you excited about starting the project in the first place.

It’s past time for Apple to start killing some darlings with the Vision Pro, but I truly hope it doesn’t go too far and kill the whole platform.

Samuel Axon is the editorial lead for tech and gaming coverage at Ars Technica. He covers AI, software development, gaming, entertainment, and mixed reality. He has been writing about gaming and technology for nearly two decades at Engadget, PC World, Mashable, Vice, Polygon, Wired, and others. He previously ran a marketing and PR agency in the gaming industry, led editorial for the TV network CBS, and worked on social media marketing strategy for Samsung Mobile at the creative agency SPCSHP. He also is an independent software and game developer for iOS, Windows, and other platforms, and he is a graduate of DePaul University, where he studied interactive media and software development.

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Crypto hoarders dump tokens as shares tumble

Bitcoin, Biz & IT, crypto, ether, syndication / Paul Patrick / November 26, 2025

“It was inevitable,” said Jake Ostrovskis, head of OTC trading at Wintermute, referring to the sell-off in digital asset treasury stocks. “It got to the point where there’s too many of them.”

Several companies have begun selling their crypto stockpiles in an effort to fund share buybacks and shore up their stock prices, in effect putting the crypto treasury model into reverse.

North Carolina-based ether holder FG Nexus sold about $41.5 million of its tokens recently to fund its share buyback program. Its market cap is $104 million, while the crypto it holds is worth $116 million. Florida-based life sciences company turned ether buyer ETHZilla recently sold about $40 million worth of its tokens, also to fund its share buyback program.

Sequans Communications, a French semiconductor company, sold about $100 million of its bitcoin this month in order to service its debt, in a sign of how some companies that borrowed to fund crypto purchases are now struggling. Sequans’ market capitalization is $87 million, while the bitcoin it holds is worth $198 million.

Georges Karam, chief executive of Sequans, said the sale was a “tactical decision aimed at unlocking shareholder value given current market conditions.”

While bitcoin and ether sellers can find buyers, companies with more niche tokens will find it more difficult to raise money from their holdings, according to Morgan McCarthy. “When you’ve got a medical device company buying some long-tail asset in crypto, a niche in a niche market, it is not going to end well,” he said, adding that 95 percent of digital asset treasuries “will go to zero.”

Strategy, meanwhile, has doubled down and bought even more bitcoin as the price of the token has fallen to $87,000, from $115,000 a month ago. The firm also faces the looming possibility of being cut from some major equity indices, which could heap even more selling pressure on the stock.

But Saylor has brushed off any concerns. “Volatility is Satoshi’s gift to the faithful,” he said this week, referring to the pseudonymous creator of bitcoin.

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There may not be a safe off-ramp for some taking GLP-1 drugs, study suggests

GLP-1, health, obesity, Tirzepatide, weight loss / Paul Patrick / November 25, 2025

Of the 308 who benefited from tirzepatide, 254 (82 percent) regained at least 25 percent of the weight they had lost on the drug by week 88. Further, 177 (57 percent) regained at least 50 percent, and 74 (24 percent) regained at least 75 percent. Generally, the more weight people regained, the more their cardiovascular and metabolic health improvements reversed.

Data gaps and potential off-ramps

On the other hand, there were 54 participants of the 308 (17.5 percent) that didn’t regain a significant amount of weight (less than 25 percent.) This group saw some of their health metrics worsen on withdrawal of the drug, but not all— blood pressure increased a bit, but cholesterol didn’t go up significantly overall. About a dozen participants (4 percent of the 308) continued to lose weight after stopping the drug.

The researchers couldn’t figure out why these 54 participants fared so well; there were “no apparent differences” in demographic or clinical characteristics, they reported. It’s clear the topic requires further study.

But, overall, the study offers a gloomy outlook for patients hoping to avoid needing to take anti-obesity drugs for the foreseeable future.

Oczypok and Anderson highlight that the study involved an abrupt withdrawal from the drug. In contrast, many patients may be interested in slowly weaning off the drugs, stepping down dosage levels over time. So far, data on this strategy and the protocols to pull it off have little data behind them. It also might not be an option for patients who abruptly lose access or insurance coverage of the drugs. Other strategies for weaning off the drugs could involve ramping up physical activity or calorie restriction in anticipation of dropping the drugs, the experts note.

In addition to more data on potential GLP-1 off-ramps, the pair calls for more data on the effects of weight fluctuations from people going on and off the treatment. At least one study has found that the regained weight after intentional weight loss may end up being proportionally higher in fat mass, which could be harmful.

For now, Oczypok and Anderson say doctors should be cautious about talking with patients about these drugs and what the future could hold. “These results add to the body of evidence that clinicians and patients should approach starting [anti-obesity medications] as long-term therapies, just as they would medications for other chronic diseases.”

There may not be a safe off-ramp for some taking GLP-1 drugs, study suggests Read More »

GPU prices are coming to earth just as RAM costs shoot into the stratosphere

AMD, gaming, intel, NAND, NVIDIA, RAM, SSDs, Tech / Paul Patrick / November 25, 2025

It’s not just PC builders

PC and phone manufacturers—and makers of components that use memory chips, like GPUs—mostly haven’t hiked prices yet. These companies buy components in large quantities, and they typically do so ahead of time, dulling the impact of the increases in the short-term. The kinds of price increases we see, and what costs are passed on to consumers, will vary from company to company.

Bloomberg reports that Lenovo is “stockpiling memory and other critical components” to get it through 2026 without issues and that the company “will aim to avoid passing on rising costs to its customers in the current quarter.” Apple may also be in a good position to weather the shortage; analysts at Morgan Stanley and Bernstein Research believe that Apple has already laid claim to the RAM that it needs and that its healthy profit margins will allow it to absorb the increases better than most.

Framework on the other hand, a smaller company known best for its repairable and upgradeable laptop designs, says “it is likely we will need to increase memory pricing soon” to reflect price increases from its suppliers. The company has also stopped selling standalone RAM kits in its online store in an effort to fight scalpers who are trying to capitalize on the shortages.

Tom’s Hardware reports that AMD has told its partners that it expects to raise GPU prices by about 10 percent starting next year and that Nvidia may have canceled a planned RTX 50-series Super launch entirely because of shortages and price increases (the main draw of this Super refresh, according to the rumor mill, would have a bump from 2GB GDDR7 chips to 3GB chips, boosting memory capacities across the lineup by 50 percent).

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China launches an emergency lifeboat to bring three astronauts back to Earth

china, human spaceflight, long march, long march 2f, shenzhou, Space, tiangong / Paul Patrick / November 25, 2025

And then, last year, Boeing’s Starliner crew capsule suffered a series of helium leaks and propulsion problems that made NASA managers uncomfortable with its ability to safely return to Earth with astronauts Butch Wilmore and Suni Williams. The two astronauts remained on the ISS as Starliner made a successful uncrewed landing in September 2024, while SpaceX launched an already-scheduled Crew Dragon mission to the station with two of its four seats unoccupied. The Dragon spacecraft brought Wilmore and Williams home in March.

The incidents with Shenzhou 20 and Soyuz MS-22 highlight the risks of space junk in low-Earth orbit, especially tiny debris fragments that evade detection by tracking telescopes and radars. A minuscule piece of space debris traveling at several miles per second can pack a punch. Crews at the Tiangong outpost ventured outside the station multiple times in the last few years to install space debris shielding to protect the outpost from such impacts.

Luckily, the damage to Shenzhou 20’s window and Soyuz MS-22’s dramatic coolant leak were unmistakable. Tiny impacts on other unseen parts of a spacecraft would be more difficult to find.

Chinese astronauts Zhang Hongzhang, Wu Fei, and Zhang Lu (left to right) attend a send-off ceremony at the Jiuquan Satellite Launch Center in northwest China before their launch on October 31, 2025. Credit: Lian Zhen/Xinhua via Getty Images

China’s first human spaceflight emergency

It has been 22 years since China sent Yang Liwei, its first astronaut, into orbit on the Shenzhou 5 mission. Since then, China’s human spaceflight program has seemingly executed its missions like clockwork. Chinese astronauts performed the program’s first spacewalk in 2008, then China launched a pair of mini-space labs in 2011 and 2016, each hosting Shenzhou crews for stays lasting several weeks.

China started launching modules for Tiangong, its first permanently occupied space station, in 2021 and completed the lab’s initial assembly in 2022. Since then, Chinese astronauts have maintained a permanent presence in low-Earth orbit.

Chinese state media previously reported that the China Manned Space Agency, managed by the country’s military, kept a rocket and Shenzhou spacecraft on standby in the event of an emergency in space. Chinese officials tapped into this rescue capability with Shenzhou 22 this month.

China’s actions with the Shenzhou program this month are evidence of a mature human spaceflight program. In parallel with operations on the Tiangong space station, China is developing new rockets, a deep space capsule, and a human-rated lunar lander to carry astronauts to the Moon by 2030.

Updated at 4 pm EST (21: 00 UTC) with more details from the China Manned Space Agency.

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Anthropic introduces cheaper, more powerful, more efficienct Opus 4.5 model

AI, Anthropic, Claude, Claude API, Claude Code, large language model, llm, Opus 4.5 / Paul Patrick / November 24, 2025

Anthropic today released Opus 4.5, its flagship frontier model, and it brings improvements in coding performance, as well as some user experience improvements that make it more generally competitive with OpenAI’s latest frontier models.

Perhaps the most prominent change for most users is that in the consumer app experiences (web, mobile, and desktop), Claude will be less prone to abruptly hard-stopping conversations because they have run too long. The improvement to memory within a single conversation applies not just to Opus 4.5, but to any current Claude models in the apps.

Users who experienced abrupt endings (despite having room left in their session and weekly usage budgets) were hitting a hard context window (200,000 tokens). Whereas some large language model implementations simply start trimming earlier messages from the context when a conversation runs past the maximum in the window, Claude simply ended the conversation rather than allow the user to experience an increasingly incoherent conversation where the model would start forgetting things based on how old they are.

Now, Claude will instead go through a behind-the-scenes process of summarizing the key points from the earlier parts of the conversation, attempting to discard what it deems extraneous while keeping what’s important.

Developers who call Anthropic’s API can leverage the same principles through context management and context compaction.

Opus 4.5 performance

Opus 4.5 is the first model to surpass an accuracy score of 80 percent—specifically, 80.9 percent in the SWE-Bench Verified benchmark, narrowly beating OpenAI’s recently released GPT-5.1-Codex-Max (77.9 percent) and Google’s Gemini 3 Pro (76.2 percent). The model performs particularly well in agentic coding and agentic tool use benchmarks, but still lags behind GPT-5.1 in visual reasoning (MMMU).

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First revealed in spy photos, a Bronze Age city emerges from the steppe

aerial archaeology, ancient cities, ancient people did stuff, Archaeology, bronze age, Kazakhstan, satellite archaeology, Science / Paul Patrick / November 22, 2025

An unexpectedly large city lies in a sea of grass inhabited largely by nomads.

This bronze ax head was found in the western half of Semiyarka. Credit: Radivojevic et al. 2025

Today all that’s left of the ancient city of Semiyarka are a few low earthen mounds and some scattered artifacts, nearly hidden beneath the waving grasses of the Kazakh Steppe, a vast swath of grassland that stretches across northern Kazakhstan and into Russia. But recent surveys and excavations reveal that 3,500 years ago, this empty plain was a bustling city with a thriving metalworking industry, where nomadic herders and traders might have mingled with settled metalworkers and merchants.

Photo of two people standing on a grassy plain under a gray sky — Radivojevic and Lawrence stand on the site of Semiyarka. Credit: Peter J. Brown

Welcome to the City of Seven Ravines

University College of London archaeologist Miljana Radivojevic and her colleagues recently mapped the site with drones and geophysical surveys (like ground-penetrating radar, for example), tracing the layout of a 140-hectare city on the steppe in what’s now Kazakhstan.

The Bronze Age city once boasted rows of houses built on earthworks, a large central building, and a neighborhood of workshops where artisans smelted and cast bronze. From its windswept promontory, it held a commanding view of a narrow point in the Irtysh River valley, a strategic location that may have offered the city “control over movement along the river and valley bottom,” according to Radivojevic and her colleagues. That view inspired archaeologists’ name for the city: Semiyarka, or City of Seven Ravines.

Archaeologists have known about the site since the early 2000s, when the US Department of Defense declassified a set of photographs taken by its Corona spy satellite in 1972, when Kazakhstan was a part of the Soviet Union and the US was eager to see what was happening behind the Iron Curtain. Those photos captured the outlines of Semiyarka’s kilometer-long earthworks, but the recent surveys reveal that the Bronze Age city was much larger and much more interesting than anyone realized.

This 1972 Corona image shows the outlines of Semiyarka’s foundations. Radivojevic et al. 2025

When in doubt, it’s potentially monumental

Most people on the sparsely populated steppe 3,500 years ago stayed on the move, following trade routes or herds of livestock and living in temporary camps or small seasonal villages. If you were a time-traveler looking for ancient cities, the steppe just isn’t where you’d go, and that’s what makes Semiyarka so surprising.

A few groups of people, like the Alekseeva-Sargary, were just beginning to embrace the idea of permanent homes (and their signature style of pottery lies in fragments all over what’s left of Semiyarka). The largest ancient settlements on the steppe covered around 30 hectares—nowhere near the scale of Semiyarka. And Radivojevic and her colleagues say that the layout of the buildings at Semiyarka “is unusual… deviating from more conventional settlement patterns observed in the region.”

What’s left of the city consists mostly of two rows of earthworks: kilometer-long rectangles of earth, piled a meter high. The geophysical survey revealed that “substantial walls, likely of mud-brick, were built along the inside edges of the earthworks, with internal divisions also visible.” In other words, the long mounds of earth were the foundations of rows of buildings with rooms. Based on the artifacts unearthed there, Radivojevic and her colleagues say most of those buildings were probably homes.

The two long earthworks meet at a corner, and just behind that intersection sits a larger mound, about twice the size of any of the individual homes. Based on the faint lines traced by aerial photos and the geophysical survey, it may have had a central courtyard or chamber. In true archaeologist fashion, Durham University archaeologist Dan Lawrence, a coauthor of the recent paper, describes the structure as “potentially monumental,” which means it may have been a space for rituals or community gatherings, or maybe the home of a powerful family.

The city’s layout suggests “a degree of architectural planning,” as Radivojevic and her colleagues put it in their recent paper. The site also yielded evidence of trading with nomadic cultures, as well as bronze production on an industrial scale. Both are things that suggest planning and organization.

“Bronze Age communities here were developing sophisticated, planned settlements similar to those of their contemporaries in more traditionally ‘urban’ parts of the ancient world,” said Lawrence.

Who put the bronze in the Bronze Age? Semiyarka, apparently

Southeast of the mounds, the ground was scattered with broken crucibles, bits of copper and tin ore, and slag (the stuff that’s left over when metal is extracted from ore). That suggested that a lot of smelting and bronze-casting happened in this part of the city. Based on the size of the city and the area apparently set aside for metalworking, Semiyarka boasted what Radivojevic and her colleagues call “a highly-organized, possibly limited or controlled, industry of this sought-after alloy.”

Bronze was part of everyday life for people on the ancient steppes, making up everything from ax heads to jewelry. There’s a reason the period from 2000 BCE to 500 BCE (mileage may vary depending on location) is called the Bronze Age, after all. But the archaeological record has offered almost no evidence of where all those bronze doodads found on the Eurasian steppe were made or who was doing the work of mining, smelting, and casting. That makes Semiyarka a rare and important glimpse into how the Bronze Age was, literally, made.

Radivojevic and her colleagues expected to find traces of earthworks or the buried foundations of mud-brick walls, similar to the earthworks in the northwest, marking the site of a big, centralized bronze-smithing workshop. But the geophysical surveys found no walls at all in the southeastern part of the city.

“This area revealed few features,” they wrote in their recent paper (archaeologists refer to buildings and walls as features), “suggesting that metallurgical production may have been dispersed or occurred in less architecturally formalized spaces.” In other words, the bronzesmiths of ancient Semiyarka seem to have worked in the open air, or in a scattering of smaller, less permanent buildings that didn’t leave a trace behind. But they all seem to have done their work in the same area of the city.

Connections between nomads and city-dwellers

East of the earthworks lies a wide area with no trace of walls or foundations beneath the ground, but with a scattering of ancient artifacts lying half-buried in the grass. The long-forgotten objects may mark the sites of “more ephemeral, perhaps seasonal, occupation,” Radivojevic and her colleagues suggested in their recent paper.

That area makes up a large chunk of the city’s estimated 140 hectares, raising questions about how many people lived here permanently, how many stopped here along trade routes or pastoral migrations, and what their relationship was like.

A few broken potsherds offer evidence that the settled city-dwellers of Semiyarka traded regularly with their more mobile neighbors on the steppe.

Within the city, most of the ceramics match the style of the Alekseevka-Sargary people. But a few of the potsherds unearthed in Semiyarka are clearly the handiwork of nomadic Cherkaskul potters, who lived on this same wide sea of grass from around 1600 BCE to 1250 BCE. It makes sense that they would have traded with the people in the city.

Along the nearby Irtysh River, archaeologists have found faint traces of several small encampments, dating to around the same time as Semiyarka’s heyday, and two burial mounds stand north of the city. Archaeologists will have to dig deeper, literally and figuratively, to piece together how Semiyarka fit into the ancient landscape.

The city has stories to tell, not just about itself but about the whole vast, open steppe and its people.

Antiquity, 2025. DOI: 10.15184/aqy.2025.10244 (About DOIs).

Kiona is a freelance science journalist and resident archaeology nerd at Ars Technica.

First revealed in spy photos, a Bronze Age city emerges from the steppe Read More »

Newest Starship booster is significantly damaged during testing early Friday

booster, explostion, Space, spacex, Starbase, starship / Paul Patrick / November 22, 2025

Friday morning’s failure was less energetic than an explosion of a Starship upper stage during testing at Massey’s in June. That incident caused widespread damage at the test site and a complete loss of the vehicle. The Booster 18 problem on Friday appeared to cause less damage to test infrastructure, and no Raptor engines had yet been installed on the vehicle.

Nevertheless, this is the point in the rocket development program at which SpaceX sought to be accelerating with development of Starship and reaching a healthy flight cadence in 2026. Many of the company’s near-term goals rely on getting Starship flying regularly and reliably.

A full view of super heavy booster 18’s catastrophic damage during testing tonight. Very significant damage to the entire LOX tank section.

11/21/25 pic.twitter.com/Kw8XeZ2qXW

— Starship Gazer (@StarshipGazer) November 21, 2025

With this upgraded vehicle, SpaceX wants to demonstrate booster landing and reuse, an upper stage tower catch next year, the beginning of operational Starlink deployment missions, and a test campaign for NASA’s Artemis Program. To keep this Moon landing program on track, it is critical that SpaceX and NASA conduct an on-orbit refueling test of Starship, which nominally was slated for the second half of 2026.

On this timeline, the company was aiming to conduct a crewed lunar landing for NASA during the second half of 2028. From an outside perspective, before this most recent failure, that timeline already seemed to be fairly optimistic.

One of the core attributes of SpaceX is that it diagnoses failure quickly, addresses problems, and gets back to flying as rapidly as possible. No doubt its engineers are already poring over the data captured Friday morning and quite possibly have already diagnosed the problem. The company is resilient, and it has ample resources.

Nevertheless, this is also a maturing program. The Starship vehicle launched for the first time in 2023, and its first stage made a successful flight two years ago. Losing the first stage of the newest generation of the vehicle, during the initial phases of testing, can only be viewed as a significant setback for a program with so much promise and so much to accomplish so soon.

Newest Starship booster is significantly damaged during testing early Friday Read More »

From defiant to contrite: Formula maker confirms bacteria amid botulism outbreak

botulism, ByHeart, Formula, health, outbreak / Paul Patrick / November 20, 2025

ByHeart announced on Thursday that its own testing identified the bacterium that causes botulism in its baby formula, which is linked to an ongoing infant botulism outbreak that has doubled since last week.

As of November 19, there have been 31 cases across 15 states—up from 15 cases in 12 states reported last week. All 31 cases so far have been hospitalized. No deaths have been reported.

The outbreak was announced on November 8, and ByHeart was, at first, unusually aggressive in deflecting blame for linked illnesses.

The link between infant botulism cases and ByHeart was first spotted by the California Department of Public Health (CDPH). The department is the world’s sole source of the infant botulism treatment BabyBIG, and, as such, is contacted when any infant botulism cases arise. CDPH started to notice a pattern of ByHeart exposure among the cases. While ByHeart products account for just 1 percent of infant formula sales, babies fed ByHeart formula accounted for 40 percent of infant botulism cases with dry formula exposure between August 1 and November 10. Soon, preliminary testing by the department identified the bacterium that causes botulism—Clostridium botulinum—in an opened can of ByHeart from one of the sick babies.

Changing tune

However, ByHeart didn’t buy it. In a video posted to social media the day the outbreak was announced, one of ByHeart’s co-founders, Mia Funt, said: “I want to make something really clear: There is no reason to believe that infant formula can cause infant botulism.” Funt claimed that “multiple regulatory bodies” have concluded that formula can’t cause infant botulism, and the US Food and Drug Administration has never found a “direct connection” between formula and infant botulism. She added that no “toxins” have been found in the formula.

From defiant to contrite: Formula maker confirms bacteria amid botulism outbreak Read More »

The EU made Apple adopt new Wi-Fi standards, and now Android can support AirDrop

android, Apple, Google Pixel, iOS, ios 26, IPhone, pixel, pixel 10, Tech / Paul Patrick / November 20, 2025

Last year, Apple finally added support for Rich Communications Services (RCS) texting to its platforms, improving consistency, reliability, and security when exchanging green-bubble texts between the competing iPhone and Android ecosystems. Today, Google is announcing another small step forward in interoperability, pointing to a slightly less annoying future for friend groups or households where not everyone owns an iPhone.

Google has updated Android’s Quick Share feature to support Apple’s AirDrop, which allows users of Apple devices to share files directly using a local peer-to-peer Wi-Fi connection. Apple devices with AirDrop enabled and set to “everyone for 10 minutes” mode will show up in the Quick Share device list just like another Android phone would, and Android devices that support this new Quick Share version will also show up in the AirDrop menu.

Google will only support this feature on the Pixel 10 series, at least to start. The company is “looking forward to improving the experience and expanding it to more Android devices,” but it didn’t announce anything about a timeline or any hardware or software requirements. Quick Share also won’t work with AirDrop devices working in the default “contacts only” mode, though Google “[welcomes] the opportunity to work with Apple to enable ‘Contacts Only’ mode in the future.” (Reading between the lines: Google and Apple are not currently working together to enable this, and Google confirmed to The Verge that Apple hadn’t been involved in this at all.)

Like AirDrop, Google notes that files shared via Quick Share are transferred directly between devices, without being sent to either company’s servers first.

Google shared a little more information in a separate post about Quick Share’s security, crediting Android’s use of the memory-safe Rust programming language with making secure file sharing between platforms possible.

“Its compiler enforces strict ownership and borrowing rules at compile time, which guarantees memory safety,” writes Google VP of Platforms Security and Privacy Dave Kleidermacher. “Rust removes entire classes of memory-related bugs. This means our implementation is inherently resilient against attackers attempting to use maliciously crafted data packets to exploit memory errors.”

The EU made Apple adopt new Wi-Fi standards, and now Android can support AirDrop Read More »

DeepMind’s latest: An AI for handling mathematical proofs

AI, Computer science, International Mathematical Olympiad, math, proofs, Science / Paul Patrick / November 19, 2025

AlphaProof can handle math challenges but needs a bit of help right now.

Computers are extremely good with numbers, but they haven’t gotten many human mathematicians fired. Until recently, they could barely hold their own in high school-level math competitions.

But now Google’s DeepMind team has built AlphaProof, an AI system that matched silver medalists’ performance at the 2024 International Mathematical Olympiad, scoring just one point short of gold at the most prestigious undergrad math competition in the world. And that’s kind of a big deal.

True understanding

The reason computers fared poorly in math competitions is that, while they far surpass humanity’s ability to perform calculations, they are not really that good at the logic and reasoning that is needed for advanced math. Put differently, they are good at performing calculations really quickly, but they usually suck at understanding why they’re doing them. While something like addition seems simple, humans can do semi-formal proofs based on definitions of addition or go for fully formal Peano arithmetic that defines the properties of natural numbers and operations like addition through axioms.

To perform a proof, humans have to understand the very structure of mathematics. The way mathematicians build proofs, how many steps they need to arrive at the conclusion, and how cleverly they design those steps are a testament to their brilliance, ingenuity, and mathematical elegance. “You know, Bertrand Russel published a 500-page book to prove that one plus one equals two,” says Thomas Hubert, a DeepMind researcher and lead author of the AlphaProof study.

DeepMind’s team wanted to develop an AI that understood math at this level. The work started with solving the usual AI problem: the lack of training data.

Math problems translator

Large language models that power AI systems like Chat GPT learn from billions upon billions of pages of text. Because there are texts on mathematics in their training databases—all the handbooks and works of famous mathematicians—they show some level of success in proving mathematical statements. But they are limited by how they operate: They rely on using huge neural nets to predict the next word or token in sequences generated in response to user prompts. Their reasoning is statistical by design, which means they simply return answers that “sound” right.

DeepMind didn’t need the AI to “sound” right—that wasn’t going to cut it in high-level mathematics. They needed their AI to “be” right, to guarantee absolute certainty. That called for an entirely new, more formalized training environment. To provide that, the team used a software package called Lean.

Lean is a computer program that helps mathematicians write precise definitions and proofs. It relies on a precise, formal programming language that’s also called Lean, which mathematical statements can be translated into. Once the translated or formalized statement is uploaded to the program, it can check if it is correct and get back with responses like “this is correct,” “something is missing,” or “you used a fact that is not proved yet.”

The problem was, most mathematical statements and proofs that can be found online are written in natural language like “let X be the set of natural numbers that…”—the number of statements written in Lean was rather limited. “The major difficulty of working with formal languages is that there’s very little data,” Hubert says. To go around it, the researchers trained a Gemini large language model to translate mathematical statements from natural language to Lean. The model worked like an automatic formalizer and produced about 80 million formalized mathematical statements.

It wasn’t perfect, but the team managed to use that to their advantage. “There are many ways you can capitalize on approximate translations,” Hubert claims.

Learning to think

The idea DeepMind had for the AlphaProof was to use the architecture the team used in their chess-, Go-, and shogi-playing AlphaZero AI system. Building proofs in Lean and Mathematics in general was supposed to be just another game to master. “We were trying to learn this game through trial and error,” Hubert says. Imperfectly formalized problems offered great opportunity for making errors. In its learning phase, AlphaProof was simply proving and disproving the problems it had in its database. If something was translated poorly, figuring out that something wasn’t right was a useful form of exercise.

Just like AlphaZero, AlphaProof in most cases used two main components. The first was a huge neural net with a few billion parameters that learned to work in the Lean environment through trial and error. It was rewarded for each proven or disproven statement and penalized for each reasoning step it took, which was a way of incentivizing short, elegant proofs.

It was also trained to use a second component, which was a tree search algorithm. This explored all possible actions that could be taken to push the proof forward at each step. Because the number of possible actions in mathematics can be near infinite, the job of the neural net was to look at the available branches in the search tree and commit computational budget only to the most promising ones.

After a few weeks of training, the system could score well on most math competition benchmarks based on problems sourced from past high school-level competitions, but it still struggled with the most difficult of them. To tackle these, the team added a third component that hadn’t been in AlphaZero. Or anywhere else.

Spark of humanity

The third component, called Test-Time Reinforcement Learning (TTRL), roughly emulated the way mathematicians approach the most difficult problems. The learning part relied on the same combination of neural nets with search tree algorithms. The difference came in what it learned from. Instead of relying on a broad database of auto-formalized problems, AlphaProof working in the TTRL mode started its work by generating an entirely new training dataset based on the problem it was dealing with.

The process involved creating countless variations of the original statement, some simplified a little bit more, some more general, and some only loosely connected to it. The system then attempted to prove or disprove them. It was roughly what most humans do when they’re facing a particularly hard puzzle, the AI equivalent of saying, “I don’t get it, so let’s try an easier version of this first to get some practice.” This allowed AlphaProof to learn on the fly, and it worked amazingly well.

At the 2024 International Mathematics Olympiad, there were 42 points to score for solving six different problems worth seven points each. To win gold, participants had to get 29 points or higher, and 58 out of 609 of them did that. Silver medals were awarded to people who earned between 22 and 28 points (there were 123 silver medalists). The problems varied in difficulty, with the sixth one, acting as a “final boss,” being the most difficult of them all. Only six participants managed to solve it. AlphaProof was the seventh.

But AlphaProof wasn’t an end-all, be-all mathematical genius. Its silver had its price—quite literally.

Optimizing ingenuity

The first problem with AlphaProof’s performance was that it didn’t work alone. To begin with, humans had to make the problems compatible with Lean before the software even got to work. And, among the six Olympic problems, the fourth one was about geometry, and the AI was not optimized for that. To deal with it, AlphaProof had to call a friend called AlphaGeometry 2, a geometry-specialized AI that ripped through the task in a few minutes without breaking a sweat. On its own, AlphaProof scored 21 points, not 28, so technically it would win bronze, not silver. Except it wouldn’t.

Human participants of the Olympiad had to solve their six problems in two sessions, four-and-a-half hours long. AlphaProof, on the other hand, wrestled with them for several days using multiple tensor processing units at full throttle. The most time- and energy-consuming component was TTRL, which battled with the three problems it managed to solve for three days each. If AlphaProof was held up to the same standard as human participants, it would basically run out of time. And if it wasn’t born at a tech giant worth hundreds of billions of dollars, it would run out of money, too.

In the paper, the team admits the computational requirements to run AlphaProof are most likely cost-prohibitive for most research groups and aspiring mathematicians. Computing power in AI applications is often measured in TPU-days, meaning a tensor processing unit working flat-out for a full day. AlphaProof needed hundreds of TPU-days per problem.

On top of that, the International Mathematics Olympiad is a high school-level competition, and the problems, while admittedly difficult, were based on things mathematicians already know. Research-level math requires inventing entirely new concepts instead of just working with existing ones.

But DeepMind thinks it can overcome these hurdles and optimize AlphaProof to be less resource-hungry. “We don’t want to stop at math competitions. We want to build an AI system that could really contribute to research-level mathematics,” Hubert says. His goal is to make AlphaProof available to the broader research community. “We’re also releasing a kind of an AlphaProof tool,” he added. “It would be a small trusted testers program to see if this would be useful to mathematicians.”

Nature, 2025. DOI: 10.1038/s41586-025-09833-y

Jacek Krywko is a freelance science and technology writer who covers space exploration, artificial intelligence research, computer science, and all sorts of engineering wizardry.

DeepMind’s latest: An AI for handling mathematical proofs Read More »

Bonkers Bitcoin heist: 5-star hotels, cash-filled envelopes, vanishing funds

Biz & IT, Security, syndication / Paul Patrick / November 18, 2025

Bitcoin mining hardware exec falls for sophisticated crypto scam to tune of $200k

As Kent Halliburton stood in a bathroom at the Rosewood Hotel in central Amsterdam, thousands of miles from home, running his fingers through an envelope filled with 10,000 euros in crisp banknotes, he started to wonder what he had gotten himself into.

Halliburton is the cofounder and CEO of Sazmining, a company that operates bitcoin mining hardware on behalf of clients—a model known as “mining-as-a-service.” Halliburton is based in Peru, but Sazmining runs mining hardware out of third-party data centers across Norway, Paraguay, Ethiopia, and the United States.

As Halliburton tells it, he had flown to Amsterdam the previous day, August 5, to meet Even and Maxim, two representatives of a wealthy Monaco-based family. The family office had offered to purchase hundreds of bitcoin mining rigs from Sazmining—around $4 million worth—which the company would install at a facility currently under construction in Ethiopia. Before finalizing the deal, the family office had asked to meet Halliburton in person.

When Halliburton arrived at the Rosewood Hotel, he found Even and Maxim perched in a booth. They struck him as playboy, high-roller types—particularly Maxim, who wore a tan three-piece suit and had a highly manicured look, his long dark hair parted down the middle. A Rolex protruded from the cuff of his sleeve.

Over a three-course lunch—ceviche with a roe garnish, Chilean sea bass, and cherry cake—they discussed the contours of the deal and traded details about their respective backgrounds. Even was talkative and jocular, telling stories about blowout parties in Marrakech. Maxim was aloof; he mostly stared at Halliburton, holding his gaze for long periods at a time as though sizing him up.

As a relationship-building exercise, Even proposed that Halliburton sell the family office around $3,000 in bitcoin. Halliburton was initially hesitant, but chalked it up as a peculiar dating ritual. One of the guys slid Halliburton the cash-filled envelope and told him to go to the bathroom, where he could count out the amount in private. “It felt like something out of a James Bond movie,” says Halliburton. “It was all very exotic to me.”

Halliburton left in a taxi, somewhat bemused by the encounter, but otherwise hopeful of closing the deal with the family office. For Sazmining, a small company with around 15 employees, it promised to be transformative.

Less than two weeks later, Halliburton had lost more than $200,000 worth of bitcoin to Even and Maxim. He didn’t know whether Sazmining could survive the blow, nor how the scammers had ensnared him.

Directly after his lunch with Even and Maxim, Halliburton flew to Latvia for a Bitcoin conference. From there, he traveled to Ethiopia to check on construction work at the data center facility.

While Halliburton was in Ethiopia, he received a WhatsApp message from Even, who wanted to go ahead with the deal on one condition: that Sazmining sell the family office a larger amount of bitcoin as part of the transaction, after the small initial purchase at the Rosewood Hotel. They landed on $400,000 worth—a tenth of the overall deal value.

Even asked Halliburton to return to Amsterdam to sign the contracts necessary to finalize the deal. Having been away from his family for weeks, Halliburton protested. But Even drew a line in the sand: “Remotely doesn’t work for me that’s not how I do business at the moment,” he wrote in a text message reviewed by WIRED.

Halliburton arrived back in Amsterdam in the early afternoon on August 16. That evening, he was due to meet Maxim at a teppanyaki restaurant at the five-star Okura Hotel. The interior is elaborately decorated in traditional Japanese style; it has wooden paneling, paper walls, a zen garden, and a flock of origami cranes that hang from string down a spiral staircase in the lobby.

Halliburton found Maxim sitting on a couch in the waiting area outside the restaurant, dressed in a gaudy silver suit. As they waited for a table, Maxim asked Halliburton whether he could demonstrate that Sazmining held enough bitcoin to go through with the side transaction that Even had proposed. He wanted Halliburton to move roughly half of the agreed amount—worth $220,000—into a bitcoin wallet app trusted by the family office. The funds would remain under Halliburton’s control, but the family office would be able to verify their existence using public transaction data.

Halliburton thumbed open his iPhone. The app, Atomic Wallet, had thousands of positive reviews and had been listed on the Apple App Store for several years. With Maxim at his side, Halliburton downloaded the app and created a new wallet. “I was trying to earn this guy’s trust,” says Halliburton. “Again, a $4 million contract. I’m still looking at that carrot.”

The dinner passed largely without incident. Maxim was less guarded this time; he talked about his fondness for watches and his work sourcing deals for the family office. Feeling under the weather from all the travel, Halliburton angled to wrap things up.

They left with the understanding that Maxim would take the signed contracts to the family office to be executed, while Halliburton would send the $220,000 in bitcoin to his new wallet address as agreed.

Back in his hotel room, Halliburton triggered a small test transaction using his new Atomic Wallet address. Then he wiped and reinstated the wallet using the private credentials—the seed phrase—generated when he first downloaded the app, to make sure that it functioned as expected. “Had to take some security measures but almost ready. Thanks for your patience,” wrote Halliburton in a WhatsApp message to Even. “No worries take your time,” Even responded.

At 10: 45 pm, satisfied with his tests, Halliburton signaled to a colleague to release $220,000 worth of bitcoin to the Atomic Wallet address. When it arrived, he sent a screenshot of the updated balance to Even. One minute later, Even wrote back, “Thank yiu [sic].”

Halliburton sent another message to Even, asking about the contracts. Though previously quick to answer, Even didn’t respond. Halliburton checked the Atomic Wallet app, sensing that something was wrong. The bitcoin had vanished.

Halliburton’s stomach dropped. As he sat on the bed, he tried to stop himself from vomiting. “It was like being punched in the gut,” says Halliburton. “It was just shock and disbelief.”

Halliburton racked his brain trying to figure out how he had been swindled. At 11: 30 pm, he sent another message to Even: “That was the most sophisticated scam I’ve ever experienced. I know you probably don’t give a shit but my business may not survive this. I’ve worked four years of my life to build it.”

Even responded, denying that he had done anything wrong, but that was the last Halliburton heard from him. Halliburton provided WIRED with the Telegram account Even had used; it was last active on the day the funds were drained. Even did not respond to a request for comment.

Within hours, the funds drained from Halliburton’s wallet began to be divided up, shuffled through a web of different addresses, and deposited with third-party platforms for converting crypto into regular currency, analysis by blockchain analytics companies Chainalysis and CertiK shows.

A portion of the bitcoin was split between different instant exchangers, which allow people to swap one type of cryptocurrency for another almost instantaneously. The bulk was funneled into a single address, where it was blended with funds tagged by Chainalysis as the likely proceeds of rip deals, a scam whereby somebody impersonates an investor to steal crypto from a startup.

“There’s nothing illegal about the services the scammer leveraged,” says Margaux Eckle, senior investigator at Chainalysis. “However, the fact that they leveraged consolidation addresses that appear very tightly connected to labeled scam activity is potentially indicative of a fraud operation.”

Some of the bitcoin that passed through the consolidation address was deposited with a crypto exchange, where it was likely swapped for regular currency. The remainder was converted into stablecoin and moved across so-called bridges to the Tron blockchain, which hosts several over-the-counter trading services that can be readily used to cash out large quantities of crypto, researchers claim.

The effect of the many hops, shuffles, conversions, and divisions is to make it more difficult to trace the origin of funds, so that they can be cashed out without arousing suspicion. “The scammer is quite sophisticated,” says Eckle. “Though we can trace through a bridge, it’s a way to slow the tracing of funds from investigators that could be on your tail.”

Eventually, the trail of public transaction data stops. To identify the perpetrators, law enforcement would have to subpoena the services that appear to have been used to cash out, which are widely required to collect information about users.

From the transaction data, it’s not possible to tell precisely how the scammers were able to access and drain Halliburton’s wallet without his permission. But aspects of his interactions with the scammers provide some clue.

Initially, Halliburton wondered whether the incident might be connected to a 2023 hack perpetrated by threat actors affiliated with the North Korean government, which led to $100 million worth of funds being drained from the accounts of Atomic Wallet users. (Atomic Wallet did not respond to a request for comment.)

But instead, the security researchers that spoke to WIRED believe that Halliburton fell victim to a targeted surveillance-style attack. “Executives who are publicly known to custody large crypto balances make attractive targets,” says Guanxing Wen, head of security research at CertiK.

The in-person dinners, expensive clothing, reams of cash, and other displays of wealth were gambits meant to put Halliburton at ease, researchers theorize. “This is a well-known rapport-building tactic in high-value confidence schemes,” says Wen. “The longer a victim spends with the attacker in a relaxed setting, the harder it becomes to challenge a later technical request.”

In order to complete the theft, the scammers likely had to steal the seed phrase for Halliburton’s newly created Atomic Wallet address. Equipped with a wallet’s seed phrase, anyone can gain unfettered access to the bitcoin kept inside.

One possibility is that the scammers, who dictated the locations for both meetings in Amsterdam, hijacked or mimicked the hotel Wi-Fi networks, allowing them to harvest information from Halliburton’s phone. “That equipment you can buy online, no problem. It would all fit inside a couple of suitcases,” says Adrian Cheek, lead researcher at cybersecurity company Coeus. But Halliburton insists that his phone never left his possession, and he used mobile data to download the Atomic Wallet app, not public Wi-Fi.

The most plausible explanation, claims Wen, is that the scammers—perhaps with the help of a nearby accomplice or a camera equipped with long-range zoom—were able to record the seed phrase when it appeared on Halliburton’s phone at the point he first downloaded the app, on the couch at the Okura Hotel.

Long before Halliburton delivered the $220,000 in bitcoin to his Atomic Wallet address, the scammers had probably set up a “sweeper script,” claims Wen, a type of automated bot coded to drain a wallet when it detects a large balance change.

The people the victim meets in-person in cases like this—like Even and Maxim—are rarely the ultimate beneficiaries, but rather mercenaries hired by a network of scam artists, who could be based on the other side of the globe.

“They’re normally recruited through underground forums, and secure chat groups,” says Cheek. “If you know where you’re looking, you can see this ongoing recruitment.”

For a few days, it remained unclear whether Sazmining would be able to weather the financial blow. The stolen funds equated to about six weeks’ worth of revenue. “I’m trying to keep the business afloat and survive this situation where suddenly we’ve got a cash crunch,” says Halliburton. By delaying payment to a vendor and extending the duration of an outstanding loan, the company was ultimately able to remain solvent.

That week, one of the Sazmining board members filed reports with law enforcement bodies in the Netherlands, the UK, and the US. They received acknowledgements from only UK-based Action Fraud, which said it would take no immediate action, and the Cyber Fraud Task Force, a division of the US Secret Service. (The CFTF did not respond to a request for comment.)

The incredible volume of crypto-related scam activity makes it all but impossible for law enforcement to investigate each theft individually. “It’s a type of threat and criminal activity that is reaching a scale that’s completely unprecedented,” says Eckle.

The best chance of a scam victim recovering their funds is for law enforcement to bust an entire scam ring, says Eckle. In that scenario, any funds recovered are typically dispersed to those who have reported themselves victims.

Until such a time, Halliburton has to make his peace with the loss. “It’s still painful,” he says. But “it wasn’t a death blow.”

This story originally appeared on Wired.

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Author name: Paul Patrick