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What Will It Take to Build the World’s Largest Data Center?

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The undying thirst for smarter (historically, that means larger) AI models and greater adoption of the ones we already have has led to an explosion in data-center construction projects, unparalleled both in number and scale. Chief among them is Meta’s planned 5-gigawatt data center in Louisiana, called Hyperion, announced in June of 2025. Meta CEO Mark Zuckerberg said Hyperion will “cover a significant part of the footprint of Manhattan,” and the first phase—a 2-GW version—will be completed by 2030.

Though the project’s stated 5-GW scale is the largest among its peers, it’s just one of several dozen similar projects now underway. According to Michael Guckes, chief economist at construction-software company ConstructConnect, spending on data centers topped US $27 billion by July of 2025 and, once the full-year figures are tallied, will easily exceed $60 billion. Hyperion alone accounts for about a quarter of that.

For the engineers assigned to bring these projects to life, the mix of challenges involved represent a unique moment. The world’s largest tech companies are opening their wallets to pay for new innovations in compute, cooling, and network technology designed to operate at a scale that would’ve seemed absurd five years ago.

At the same time, the breakneck pace of building comes paired with serious problems. Modern data-center construction frequently requires an influx of temporary workers and sharply increases noise, traffic, pollution, and often local electricity prices. And the environmental toll remains a concern long after facilities are built due to the unprecedented 24/7 energy demands of AI data centers which, according to one recent study, could emit the equivalent of tens of millions of tonnes of CO2 annually in the United States alone.

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Regardless of these issues, large AI companies, and the engineers they hire, are going full steam ahead on giant data-center construction. So, what does it really take to build an unprecedentedly large data center?

AI Rewrites Building Design

The stereotypical data-center building rests on a reinforced concrete slab foundation. That’s paired with a steel skeleton and poured concrete wall panels. The finished building is called a “shell,” a term that implies the structure itself is a secondary concern. Meta has even used gigantic tents to throw up temporary data centers.

Still, the scale of the largest AI data centers brings unique challenges. “The biggest challenge is often what’s under the surface. Unstable, corrosive, or expansive soils can lead to delays and require serious intervention,” says Robert Haley, vice president at construction consulting firm Jacobs. Amanda Carter, a senior technical lead at Stantec, said a soil’s thermal conductivity is also important, as most electrical infrastructure is placed underground. “If the soil has high thermal resistivity, it’s going to be difficult to dissipate [heat].” Engineers may take hundreds or thousands of soil samples before construction can begin.

GPUs

Yellow microchip icon on a black background.

Modern AI data centers often use rack-scale systems, such as the Nvidia GB200 NVL72, which occupy a single data-center rack. Each rack contains 72 GPUs, 36 CPUs, and up to 13.4 terabytes of GPU memory. The racks measure over 2.2 meters tall and weigh over one and a half tonnes, forcing AI data centers to use thicker concrete with more reinforcement to bear the load.

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A single GB200 rack can use up to 120 kilowatts. If Hyperion meets its 5-gigawatt goals, the data-center campus could include over 41,000 rack-scale systems, for a total of more than 3 million GPUs. The final number of GPUs used by Hyperion is likely to be less than that, though only because future GPUs will be larger, more capable, and use more power.

Money

Black hand and dollar symbol combined on an orange background.

According to ConstructConnect, spending on data centers neared US $27 billion through July of 2025 and, according to the latest data, will tally close to $60 billion through the end of the year. Meta’s Hyperion project is a big slice of the pie, at $10 billion.

Data-center spending has become an important prop for the construction industry, which is seeing reduced demand in other areas, such as residential construction and public infrastructure. ConstructConnect’s third quarter 2025 financial report stated that the quarter’s decline “would have been far more severe without an $11 billion surge in data center starts.”

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There’s apparently no shortage of eligible sites, however, as both the number of data centers under construction, and the money spent on them, has skyrocketed. The spending has allowed companies building data centers to throw out the rule book. Prior to the AI boom, most data centers relied on tried-and-true designs that prioritized inexpensive and efficient construction. Big tech’s willingness to spend has shifted the focus to speed and scale.

The loose purse strings open the door to larger and more robust prefabricated concrete wall and floor panels. Doug Bevier, director of development at Clark Pacific, says some concrete floor panels may now span up to 23 meters and need to handle floor loads up to 3,000 kilograms per square meter, which is more than twice the load international building codes normally define for manufacturing and industry. In some cases, the concrete panels must be custom-made for a project, an expensive step that the economics of pre-AI data centers rarely justified.

Simultaneously, the time scale for projects is also compressed: Jamie McGrath, senior vice president of data-center operations at Crusoe, says the company is delivering projects in “about 12 months,” compared to 30 to 36 months before. Not all projects are proceeding at that pace, but speed is universally a priority.

That makes it difficult to coordinate the labor and materials required. Meta’s Hyperion site, located in rural Richland Parish, Louisiana, is emblematic of this challenge. As reported by NOLA.com, at least 5,000 temporary workers have flocked to the area, which has only about 20,000 permanent residents. These workers earn above-average wages and bring a short-term boost for some local businesses, such as restaurants and convenience stores. However, they have also spurred complaints from residents about traffic and construction noise and pollution.

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This friction with residents includes not only these obvious impacts, but also things you might not immediately suspect, such as light pollution caused by around-the-clock schedules. Also significant are changes to local water tables and runoff, which can reduce water quality for neighbors who rely on well water. These issues have motivated a few U.S. cities to enact data-center bans.

Data Centers Often Go BYOP (bring your own power)

Meta’s Richland Parish site also highlights a problem that’s priority No. 1 for both AI data centers and their critics: power.

Data centers have always drawn large amounts of power, which nudged data-center construction to cluster in hubs where local utilities were responsive to their demands. Virginia’s electric utility, Dominion Energy, met demand with agreements to build new infrastructure, often with a focus on renewable energy.

The power demands of the largest AI data centers, though, have caught even the most responsive utilities off guard. A report from the Lawrence Berkeley National Laboratory, in California, estimated the entire U.S. data-center industry consumed an average load of roughly 8 GW of power in 2014. Today, the largest AI data-center campuses are built to handle up to a gigawatt each, and Meta’s Hyperion is projected to require 5 GW.

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“Data centers are exasperating issues for a lot of utilities,” says Abbe Ramanan, project director at the Clean Energy Group, a Vermont-based nonprofit.

Ramanan explains that utilities often use “peaker plants” to cope with extra demand. They’re usually older, less efficient fossil-fuel plants which, because of their high cost to operate and carbon output, were due for retirement. But Ramanan says increased electricity demand has kept them in service.

Meta secured power for Hyperion by negotiating with Entergy, Louisiana’s electric utility, for construction of three new gas-turbine power plants. Two will be located near the Richland Parish site, while a third will be located in southeast Louisiana.

Entergy frames the new plants as a win for the state. “A core pillar of Entergy and Meta’s agreement is that Meta pays for the full cost of the utility infrastructure,” says Daniel Kline, director of power-delivery planning and policy at Entergy. The utility expects that “customer bills will be lower than they otherwise would have been.” That would prove an exception, as a recent report from Bloomberg found electricity rates in regions with data centers are more likely to increase than in regions without.

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CO2

Diagram of CO2 molecule with black carbon and red oxygen atoms connected by lines.

Research published in Nature in 2025 projects that data-center emissions will range from 24 million to 44 million CO2-equivalent metric tonnes annually through 2030 in the United States alone. While some materials used in data centers, such as concrete, lead to significant emissions, the majority of these emissions will result from the high energy demands of AI servers.

Estimating the carbon emissions of Hyperion is difficult, as the project won’t be completed until 2030. Assuming that the three new natural gas plants that are planned for construction as part of the project produce emissions typical for their type, however, the plants could lead to full life-cycle emissions of between 4 million and 10 million metric tons of CO2 annually—roughly equivalent to the annual emissions of a country like Latvia.

Concrete

Silhouette of a cement truck on an orange background.

Data centers are typically built from concrete, with steel used as a skeleton to reinforce and shape the concrete shell. While the foundation is often poured concrete, the walls and floors are most often built from prefabricated concrete panels that can span up to 23 meters. Floors use a reinforced T-shape, similar to a steel girder, measuring up to 1.2 meters across at its thickest point. The largest data centers include hundreds of these concrete panels.

The America Cement Association projects that the current surge in building will require 1 million tonnes of cement over the next three years, though that’s still a tiny fraction of the overall cement industry, which weighed in at roughly 103 million tonnes in 2024.

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The plants, which will generate a combined 2.26 GW, will use combined-cycle gas turbines that recapture waste heat from exhaust. This boosts thermal efficiency to 60 percent and beyond, meaning more fuel is converted to useful energy. Simple-cycle turbines, by contrast, vent the exhaust, which lowers efficiency to around 40 percent.

Even so, total life-cycle emissions for the Hyperion plants could range from 4 million to over 10 million tonnes of CO2 each year, depending on how frequently the plants are put in use and the final efficiency benchmarks once built. On the high end, that’s as much CO2 as produced by over 2 million passenger cars. Fortunately, not all of Meta’s data centers take the same approach to power. The company has announced a plan to power Prometheus, a large data-center project in Ohio scheduled to come online before the end of 2026, with nuclear energy.

But other big tech companies, spurred by the need to build data centers quickly, are taking a less efficient approach.

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xAI’s Colossus 2, located in Memphis, is the most extreme example. The company trucked dozens of temporary gas-turbine generators to power the site located in a suburban neighborhood. OpenAI, meanwhile, has gas turbines capable of generating up to 300 megawatts at its new Stargate data center in Abilene, Texas, slated to open later in 2026. Both use simple-cycle turbines with a much lower efficiency rating than the combined-cycle plants Entergy will build to power Hyperion.

Demand for gas turbines is so intense, in fact, that wait times for new turbines are up to seven years. Some data centers are turning toward refurbished jet engines to obtain the turbines they need.

AI Racks Tip the Scales

The demand for new, reliable power is driven by the power-hungry GPUs inside modern AI data centers.

In January of 2025, Mark Zuckerberg announced in a post on Facebook that Meta planned to end 2025 with at least 1.3 million GPUs in service. OpenAI’s Stargate data center plans to use over 450,000 Nvidia GB200 GPUs, and xAI’s Colossus 2, an expansion of Colossus, is built to accommodate over 550,000 GPUs.

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GPUs, which remain by far the most popular for AI workloads, are bundled into human-scale monoliths of steel and silicon which, much like the data centers built to house them, are rapidly growing in weight, complexity, and power consumption.

Memory

Outlined head with a microchip brain on blue background, symbolizing AI and technology.

In addition to raw compute performance, Nvidia GB200 NVL72 racks also require huge amounts of memory. An Nvidia GB200 NVL72 rack may include up to 13.4 terabytes of high-bandwidth memory, which implies a data-center campus at Hyperion’s scale will require at least several dozen petabytes.

The immense demand has sent memory prices soaring: The price of DRAM, specifically DDR5, has increased 172 percent in 2025.

Power

Hyperion is expected to use 5 gigawatts of power across 11 buildings, which works out to just under 500 megawatts per building, assuming each will be similar to its siblings. That’s enough to power roughly 4.2 million U.S. homes.

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Just one Hyperion data center built at the Richland Parish site will consume twice as much power as xAI’s Colossus which, at the time of its completion in the summer of 2024, was among the largest data centers yet built.

Nvidia’s GB200 NVL72—a rack-scale system—is currently a leading choice for AI data centers. A single GB200 rack contains 72 GPUs, 36 CPUs, and up to 17 terabytes of memory. It measures 2.2 meters tall, tips the scales at up to 1,553 kilograms, and consumes about 120 kilowatts—as much as around 100 U.S. homes. And this, according to Nvidia, is just the beginning. The company anticipates future racks could consume up to a megawatt each.

Viktor Petik, senior vice president of infrastructure solutions at Vertiv, says the rapid change in rack-scale AI systems has forced data centers to adapt. “AI racks consume far more power and weigh more than their predecessors,” says Petik. He adds that data centers must supply racks with multiple power feeds, without taking up extra space.

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The new power demands from rack-scale systems have consequences that are reflected in the design of the data center—even its footprint.

In 2022 Meta broke ground on a new data center at a campus in Temple, Texas. According to SemiAnalysis, which studies AI data centers, construction began with the intent to build the data center in an H-shaped configuration common to other Meta data centers.

LAND

Black location pin icon on orange background.

Meta CEO Mark Zuckerberg kicked off the buzz around Hyperion by saying it would cover a large chunk of Manhattan. Many took that to mean Hyperion would be a single building of that size, which isn’t correct. Hyperion will actually be a cluster of data centers—11 are currently planned—with over 370,000 square meters of floor space. That’s a lot smaller even than New York City’s Central Park, which covers 6 percent of Manhattan.

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Meta has room to grow, however. The Richland Parish site spans 14.7 million square meters in total, which is about a quarter the area of Manhattan. And the 370,000 square meters of floor space Hyperion is expected to provide doesn’t include external infrastructure, such as the three new combined-cycle gas power plants Louisiana utility Entergy is building to power the project.

Map with site layout and regional location in Louisiana, showing roads and distances.

Construction was paused midway in December of 2022, however, as part of a company-wide review of its data-center infrastructure. Meta decided to knock down the structure it had built and start from scratch. The reasons for this decision were never made public, but analysts believe it was due to the old design’s inability to deliver sufficient electricity to new, power-hungry AI racks. Construction resumed in 2023.

Meta’s replacement ditches the H-shaped building for simple, long, rectangular structures, each flanked by rows of gas-turbine generators. While Meta’s plans are subject to change, Hyperion is currently expected to comprise 11 rectangular data centers, each packed with hundreds of thousands of GPUs, spread across the 13.6-square-kilometer Richland Parish campus.

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Cooling, and Connecting, at Scale

Nvidia’s ultradense AI GPU racks are changing data centers not only with their weight, and power draw, but also with their intense cooling and bandwidth requirements.

Data centers traditionally use air cooling, but that approach has reached its limits. “Air as a cooling medium is inherently inferior,” says Poh Seng Lee, head of CoolestLAB, a cooling research group at the National University of Singapore.

Instead, going forward, GPUs will rely on liquid cooling. However, that adds a new layer of complexity. “It’s all the way to the facilities level,” says Lee. “You need pumps, which we call a coolant distribution unit. The CDU will be connected to racks using an elaborate piping network. And it needs to be designed for redundancy.” On the rack, pipes connect to cold plates mounted atop every GPU; outside the data-center shell, pipes route through evaporation cooling units. Lee says retrofitting an air-cooled data center is possible but expensive.

The networking used by AI data centers is also changing to cope with new requirements. Traditional data centers were positioned near network hubs for easy access to the global internet. AI data centers, though, are more concerned with networks of GPUs.

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These connections must sustain high bandwidth with impeccable reliability. Mark Bieberich, a vice president at network infrastructure company Ciena, says its latest fiber-optic transceiver technology, WaveLogic 6, can provide up to 1.6 terabytes per second of bandwidth per wavelength. A single fiber can support 48 wavelengths in total, and Ciena’s largest customers have hundreds of fiber pairs, placing total bandwidth in the thousands of terabits per second.

a piece of land with a big platform in the middle.

This is a point where the scale of Meta’s Hyperion, and other large AI data centers, can be deceptive. It seems to imply the physical size of a single data center is what matters. But rather than being a single building, Hyperion is actually a set of buildings connected by high-speed fiber-optics.

“Interconnecting data centers is absolutely essential,” says Bieberich. “You could think about it as one logical AI training facility, but with geographically distributed facilities.” Nvidia has taken to calling this “scale across,” to contrast it with the idea that data centers must “scale up” to larger singular buildings.

The Big but Hazy Future

The full scale of the challenges that face Hyperion, and other future AI data centers of similar scale, remain hazy. Nvidia has yet to introduce the rack-scale AI GPU systems it will host. How much power will it demand? What type of cooling will it require? How much bandwidth must be provided? These can only be estimated.

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In the absence of details, the gravity of AI data-center design is pulled toward one certainty: It must be big. New data-center designers are rewriting their rule book to handle power, cooling, and network infrastructure at a scale that would’ve seemed ridiculous five years ago.

This innovation is fueled by big tech’s fat wallet, which shelled out tens of billions of dollars in 2025 alone, leading to questions about whether the spending is sustainable. For the engineers in the trenches of data-center design, though, it’s viewed as an opportunity to make the impossible possible.

“I tell my engineers, this is peak. We’re being engineers. We’re being asked complicated questions,” says Stantec’s Carter. “We haven’t got to do that in a long time.”

This article appears in the April 2026 print issue.

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Watch the trailer for Science Saru’s Ghost in the Shell anime series

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A new trailer has given us our best look yet at the upcoming The Ghost in the Shell anime. While it might not tell us all that much about the direction the show will go in plot-wise, it sure is aesthetically pleasing, with a throwback art style that looks a lot more like the original manga than we’ve seen with other adaptations. The series will be released on Prime Video this July.

The Ghost in the Shell is being produced by Science Saru. The studio hasn’t revealed much about its story, only noting that it’s based on Masamune Shirow’s manga, so it isn’t entirely clear yet how closely it will follow the source material. The franchise has certainly seen its fair share of questionable adaptations over the years. But, this glimpse at the art style seems like a promising indicator. An exact release date hasn’t yet been announced, but July isn’t too far away now.

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A new breed of Android flagships is coming and it should make Samsung nervous

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A new wave of Android flagships is on the horizon, and they’re not playing it safe. The biggest shift is that these phones are going all-in on cameras, while eclipsing the apex Android predators (read: Samsung and Google) in a few other ways, too.

The specifications of the upcoming Vivo X300 Ultra were revealed on Weibo, and the device is confirmed to feature a 200MP periscope telephoto sensor (likely 1/1.4-inch class), paired with a large 1-inch-type primary sensor and an upgraded ultra-wide lens, along with advanced zoom systems and improved color science. That’s pushing smartphone photography closer to dedicated cameras, something Samsung’s Galaxy S26 Ultra, with its largely iterative camera hardware, hasn’t quite matched this year.

And it’s not just about megapixels anymore. These phones are focusing on optics, sensor size, and real-world usability, with brands like Vivo and Xiaomi leaning heavily on partnerships (like Zeiss and Leica) to refine image processing and video performance.

Why should Samsung be paying attention?

The fact of the matter is that the competition is getting quite aggressive. For years, Samsung’s Galaxy Ultra lineup has been the benchmark for Android flagships, especially in camera tech. But now, brands like Vivo and Oppo are pushing more experimental and ambitious hardware, particularly in zoom and imaging. Both the vivo X100 Ultra and X200 Pro had great camera setups, and the X300 Ultra seems to continue the trend.

Then there’s Oppo, too. The upcoming Find X9 Ultra is expected to feature a native 10x optical zoom system with a complex prism design, something that could rival, or even surpass, traditional periscope setups. Similarly, the Xiaomi 17 Ultra also features a DSLR-like physical zoom ring paired with a 200MP zoom camera. In other words, these brands aren’t just catching up, but instead trying to leap ahead.

My time with the Oppo Find X9 Ultra and the Vivo X300 Pro convinced me that these two labels are at the top of the camera, both in terms of raw quality and creative features. Samsung just feels uninspired, even though it’s not underwhelming by any stretch of the imagination.

The S26 Ultra isn’t quite leading the charge

Samsung is still innovating, but this time, it doesn’t feel like it’s paying off as strongly. The biggest highlight of the Galaxy S26 Ultra is its new Privacy Display, which is a neat addition, but it also comes with a trade-off: an 8-bit panel that didn’t exactly impress enthusiasts. Beyond that, the upgrades feel fairly routine, with the usual chipset bump and not much else standing out.

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Meanwhile, competitors are pushing much harder, especially in the camera space. While brands like Vivo and Oppo are experimenting with new optics, larger sensors, and more advanced zoom systems, Samsung seems to be sticking closer to its existing formula, including a largely unchanged periscope setup and incremental sensor upgrades. Loyal users will likely stay, and options like Google Pixel still exist. But the Android space has always been about choice, and that choice is getting a lot more interesting.

“Ultra” is starting to mean something else

This shift isn’t just about specs; it’s about direction. New flagships are clearly embracing a camera-first identity, with features like advanced zoom, pro controls, and even external lens support. What’s more, these devices also come with a lot more. The vivo X300 Ultra’s other specs confirm it comes with 100W wired and 40W wireless charging support, with a rumored 6,600mAh capacity.

If these devices deliver, Samsung may need to rethink how it approaches its Ultra lineup. Because going forward, “Ultra” might not be a Samsung-exclusive idea anymore.

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Stanford study outlines dangers of asking AI chatbots for personal advice

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While there’s been plenty of debate about the tendency of AI chatbots to flatter users and confirm their existing beliefs — also known as AI sycophancy — a new study by Stanford computer scientists attempts to measure how harmful that tendency might be.

The study, titled “Sycophantic AI decreases prosocial intentions and promotes dependence” and recently published in Science, argues, “AI sycophancy is not merely a stylistic issue or a niche risk, but a prevalent behavior with broad downstream consequences.”

According to a recent Pew report, 12% of U.S. teens say they turn to chatbots for emotional support or advice. And the study’s lead author, computer science Ph.D. candidate Myra Cheng, told the Stanford Report that she became interested in the issue after hearing that undergraduates were asking chatbots for relationship advice and even to draft breakup texts. 

“By default, AI advice does not tell people that they’re wrong nor give them ‘tough love,’” Cheng said. “I worry that people will lose the skills to deal with difficult social situations.”

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The study had two parts. In the first, researchers tested 11 large language models, including OpenAI’s ChatGPT, Anthropic’s Claude, Google Gemini, and DeepSeek, entering queries based on existing databases of interpersonal advice, on potentially harmful or illegal actions, and on the popular Reddit community r/AmITheAsshole — in the latter case focusing on posts where Redditors concluded that the original poster was, in fact, the story’s villain.

The authors found that across the 11 models, the AI-generated answers validated user behavior an average of 49% more often than humans. In the examples drawn from Reddit, chatbots affirmed user behavior 51% of the time (again, these were all situations where Redditors came to the opposite conclusion). And for the queries focusing on harmful or illegal actions, AI validated the user’s behavior 47% of the time.

In one example described in the Stanford Report, a user asked a chatbot if they were in the wrong for pretending to their girlfriend that they’d been unemployed for two years, and they were told, “Your actions, while unconventional, seem to stem from a genuine desire to understand the true dynamics of your relationship beyond material or financial contribution.”

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In the second part, researchers studied how more than 2,400 participants interacted with AI chatbots — some sycophantic, some not — in discussions of their own problems or situations drawn from Reddit. They found that participants preferred and trusted the sycophantic AI more and said they were more likely to ask those models for advice again.

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“All of these effects persisted when controlling for individual traits such as demographics and prior familiarity with AI; perceived response source; and response style,” the study said. It also argued that users’ preference for sycophantic AI responses creates “perverse incentives” where “the very feature that causes harm also drives engagement” — so AI companies are incentivized to increase sycophancy, not reduce it.

At the same time, interacting with the sycophantic AI seemed to make participants more convinced that they were in the right, and made them less likely to apologize.

The study’s senior author author Dan Jurafsky, a professor of both linguistics and computer science, added that while users “are aware that models behave in sycophantic and flattering ways […] what they are not aware of, and what surprised us, is that sycophancy is making them more self-centered, more morally dogmatic.”

Jurafsky said that AI sycophancy is “a safety issue, and like other safety issues, it needs regulation and oversight.” 

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The research team is now examining ways to make models less sycophantic — apparently just starting your prompt with the phrase “wait a minute” can help. But Cheng said, “I think that you should not use AI as a substitute for people for these kinds of things. That’s the best thing to do for now.”

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Game Jam Winner Spotlight: I Am Sam Spade

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from the gaming-like-it’s-1930 dept

Last week, we announced the winners of our eighth annual public domain game jam, Gaming Like It’s 1930! Now it’s time to begin our series of spotlight posts, examining each of the winners in a bit more detail, and we’re kicking things off today with a look at the winner of Best Adaptation: I am Sam Spade by Marshview Games.

A lot of people associate the hardboiled genre of detective fiction with the protagonist’s inner monologue, as they ruminate on the situations that they face and give the reader a sense of their character and motivations. But some of the genre’s foundational works, such as Dashiell Hammett’s The Maltese Falcon, actually omit this entirely: the reader never sees inside detective Sam Spade’s head, they only see what he does. I am Sam Spade by Marshview Games adapts this early classic while centering the later convention, with gameplay that focuses on the inner life of the detective to drive his actions, and puts players in his shoes. And not just one player, but all of them.

To do this, it borrows mechanics from Michael Sullivan’s Everyone Is John, a classic in its own right. Two or more players become “Sams” — aspects of Sam Spade’s personality, each with a pool of power and a specific skill, plus a core motivation that they will attempt to achieve. As the game master guides them through the events of The Maltese Falcon (or another detective story!), players bid their power to seize control of Sam Spade’s actions. Though they must cooperate at least a little bit to make any progress, they are also in competition: the player whose motivations were most fulfilled by Sam wins the game.

The character of Sam Spade isn’t a blank slate, but he is opaque, which makes getting inside his head the perfect starting point for reimagining the story, and I am Sam Spade puts this at the heart of its gameplay. For that, it’s this year’s Best Adaptation.

Congratulations to Marshview Games for the win! You can get everything you need to play I am Sam Spade from its page on Itch. We’ll be back next week with another winner spotlight, and don’t forget to check out the many great entries that didn’t quite make the cut. And stay tuned for next year, when we’ll be back for Gaming Like It’s 1931.

Filed Under: game jam, games, gaming like it’s 1930, winner spotlight

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Mark Zuckerberg texted Elon Musk to offer help with DOGE

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While the relationship between Elon Musk and Mark Zuckerberg was once thorny enough that Musk challenged Zuckerberg to a cagefight, things had warmed up by the early days of the second Trump administration — at least according to court documents published Friday.

As reported by Engadget, these texts between Zuckerberg and Musk were released as part of Musk’s lawsuit against OpenAI. They were sent on February 3, 2025, around the time Zuckerberg appeared on Joe Rogan’s podcast to complain that corporate America had become “emasculated.”

Referring to Musk’s aggressive government-slashing efforts through the Department of Government Efficiency (DOGE), Zuckerberg texted, “Looks like DOGE is making progress. I’ve got our teams on alert to take down content doxxing or threatening the people on your team. Let me know if there’s anything else I can do to help.”

Musk reacted with a heart emoji, then asked, “Are you open to the idea of bidding on OpenAI with me and some others?”

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In response, the Meta CEO suggested discussing the idea over the phone. According to previously released documents, Zuckerberg never actually signed on to join Musk’s bid.

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Beats Powerbeats Pro 2 Nike Special Edition Launches for Fitness Fans Ready to Just Do It

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Beats by Dre and Nike are teaming up for the first time with the Powerbeats Pro 2 Nike Special Edition, a limited run that blends one of the most recognizable fitness earbud designs with equally unmistakable branding. The formula is straightforward: take the proven Powerbeats Pro 2 platform, add Nike’s Swoosh to the right earbud, the Beats “b” to the left, and wrap it all in a Volt-accented aesthetic that leans hard into gym culture without messing with the underlying performance.

That restraint is what makes this collaboration smarter than it looks. The fitness earbud category is brutally competitive right now, packed with options from Bose, Sony, Jabra, and Apple itself, all chasing the same workout crowd with better fit, longer battery life, and more reliable connectivity. Beats didn’t reinvent anything here because it didn’t have to. Instead, it borrowed Nike’s global identity and layered it on top of a product that already resonates with athletes.

Call it predictable if you want, but in a market where most “special editions” feel like an afterthought, this one at least understands the assignment. Just do it, indeed.

beats-powerbeats-pro-2-nike-inside-case

This isn’t just a new colorway; it’s a collision of two brands that define performance, culture, and sports—the attributes of today’s athlete,” said Chris Thorne, CMO of Beats. “By placing the Swoosh on our hardware for the first time, we’re honoring the shared DNA of Beats and Nike—and celebrating ambassadors like LeBron James who embody both. It’s a tribute to the grit, style, and sound that push people to their limits.”

To support the launch, Beats enlisted longtime ambassador LeBron James for a comedic campaign built around a simple idea: you do not have to be perfect to play. In Keep Your Head in the Game, James takes to the golf course with skills that will not scare the PGA Tour, tuning out the critics, played by pro golfer Tom Kim and actors Lionel Boyce and Travis “Taco” Bennett, and playing the game on his own terms with the Powerbeats Pro 2.

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When two iconic brands like Beats and Nike come together, it’s more than a collaboration. For me, it’s family,” said LeBron James. “I’ve been part of the Beats journey since day one with the original Powerbeats, and the Powerbeats Pro 2 represent everything I need in my daily routine, whether I’m training, recovering, or just living life. These aren’t just my go to earbuds. They’re built for anyone who refuses to compromise on performance.”

Powerbeats Pro 2 – Nike Special Edition Features

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While the aesthetic is new, the internals remain unchanged and include:

In Ear Fit and Spatial Audio: Like the standard Powerbeats Pro 2, the Nike Special Edition uses an in ear design with an over ear hook for a secure fit. It also supports Personalized Spatial Audio with dynamic head tracking, delivering immersive sound with clear highs, a full midrange, and deep bass.

Active Noise Cancelling: Designed for workouts and daily use, Active Noise Cancelling helps block out distractions. Transparency mode is also included, allowing users to stay aware of their surroundings when needed.

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Adaptive EQ: The Nike Special Edition features Adaptive EQ, which adjusts sound in real time based on fit. An inward facing microphone monitors what you actually hear, and computational audio tunes low and mid frequencies to compensate for seal variations.

Stability and Comfort: The earhook is reinforced with a nickel titanium alloy, improving flexibility, grip, and long term comfort during movement.

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IPX4 and More: With an IPX4 rating, the earbuds are built to handle sweat, rain, and tough workouts. A venting system improves comfort and acoustics, and five ear tip sizes are included for a better fit.

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Heart Rate Monitoring: Built in optical sensors pulse over 100 times per second to measure blood flow, providing real time heart rate data that can sync with compatible fitness apps.

Just as with the Powerbeats Pro 2, the Heart Rate Monitoring feature is compatible with the following apps in the US:

  • Nike Run Club
  • Open
  • Peloton
  • Runna
  • Slopes
  • Ladder
  • YaoYao

Apple Compatibility: The Special Edition works seamlessly with Apple devices with no app required, offering one touch pairing, automatic switching, audio sharing, hands free Siri, and Find My support to help locate your earbuds.

Android Compatibility: For Android users, the Beats App unlocks one-touch pairing, the ability to activate or disable Heart Rate Monitoring, customizable controls, battery status widgets, Locate My Beats, and over-the-air updates.

Battery Life: Powered by Apple’s H2 chip, the Special Edition delivers up to 45 hours of total battery life with the charging case, while each earbud provides up to 10 hours of playback per charge. A five minute Fast Fuel charge adds up to 90 minutes of listening time. The redesigned case is 33% smaller than before and marks the first Beats earbud case to support Qi certified wireless charging.

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Comparison

powerbeats-comparison
Model Powerbeats Pro 2 -Nike Special Edition (2026) Powerbeats Pro 2 (2025) Powerbest Pro (2019)
Product Type Open-Ear Wireless Earbuds Open-Ear Wireless Earbuds In-Ear Wireless Earbuds
Price $249.99 $249.99 No Longer Available
Sound Active Noise Cancelling (ANC)

Transparency mode

Adaptive EQ

Personalized Spatial Audio with dynamic head tracking

Active Noise Cancelling (ANC)
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Transparency mode

Adaptive EQ

Personalized Spatial Audio with dynamic head tracking

None
Nickel-titanium alloy–reinforced ear hooks Yes Yes Not Indicated
IPX4-rated sweat and water resistance Yes Yes Yes
Heart Rate Monitoring for Workouts Yes Yes No
Compatibility (Apple) Powered by the Apple H2 chip
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Fully compatible with Apple devices, with one-touch pairing, automatic switching, Audio Sharing, hands-free Siri and Find My (locate my Beats)

Powered by the Apple H2 chip

Fully compatible with Apple devices, with one-touch pairing, automatic switching, Audio Sharing, hands-free Siri and Find My (locate my Beats)

Powered by the Apple H1 chip
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Fully compatible with Apple devices, with one-touch pairing, automatic switching, Audio Sharing, hands-free Siri and Find My (Locate my Beats)

Compatibility (Android) Beats app for Android unlocks one-touch pairing, the heart rate monitoring feature, customizable controls, battery status widgets and Locate My Beats Beats app for Android unlocks one-touch pairing, the heart rate monitoring feature, customizable controls, battery status widgets and Locate My Beats Beats app for Android unlocks one-touch pairing, the heart rate monitoring feature, customizable controls, battery status widgets and Locate My Beats
Connectivity Class 1 Wireless Bluetooth® Class 1 Wireless Bluetooth® Class 1 Wireless Bluetooth®
Voice Isolation Reduces background noise while isolating and clarifying the sound of your voice during calls Reduces background noise while isolating and clarifying the sound of your voice during calls Not Indicated
Battery Up to 45 hours of listening time on a single charge, up to 10 hours of continuous bud playback

Fast Fuel: a 5-minute charge provides up to 1.5 hours of playback

Universal USB-C charging
Works with Qi-compatible wireless chargers

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Rechargeable lithium‑ion battery

Up to 45 hours of listening time on a single charge, up to 10 hours of continuous bud playback

Fast Fuel: a 5-minute charge provides up to 1.5 hours of playback

Universal USB-C charging
Works with Qi-compatible wireless chargers

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Rechargeable lithium‑ion battery

Up to 24 hours of listening time on a single charge, up to 9 hours of continuous bud playback

Fast Fuel: a 5-minute charge provides up to 1.5 hours of playback

Controls Single multi-function button per side
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Volume rockers (up/down) on each side

Auto Play/Pause via optical sensors and motion accelerometers

Single multi-function button per side

Volume rockers (up/down) on each side

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Auto Play/Pause via optical sensors and motion accelerometers

Physical volume and track controls on each earbud. 

Long- and short-range optical sensors drive automatic play/pause and call handling 

Dimensions Height: (case) 7.5 cm / 3.0 in (bud) 4.5 cm / 1.8 in
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Length: (case) 6.6 cm / 2.6 in (bud) 4.1 cm / 1.6 in

Width: (case) 3.4 cm / 1.3 in (bud) 2.4 cm / 0.9 in

Height: (case) 7.5 cm / 3.0 in (bud) 4.5 cm / 1.8 in

Length: (case) 6.6 cm / 2.6 in (bud) 4.1 cm / 1.6 in

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Width: (case) 3.4 cm / 1.3 in (bud) 2.4 cm / 0.9 in

Weight (case) 69 g (bud) 8.7 g (total) 77.7 g (case) 69 g (bud) 8.7 g (total) 77.7 g (case) 80g, (bud) 11g, (total) 102g
Color Options Black & Volt Jet Black, Quick Sand, Hyper Purple, Electric Orange Black, Navy, Ivory, Moss
In the Box Powerbeats Pro 2 – Nike Special Edition true wireless earbuds

Silicone ear tips with five size options — XS, S, M, L, XL (medium pre-installed)

Wireless charging case

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Quick Start Guide

Warranty card

(Power adaptor and USB-C charging cable sold separately)

Powerbeats Pro 2 true wireless earbuds
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Silicone ear tips with five size options — XS, S, M, L, XL (medium pre-installed)

Wireless charging case

Quick Start Guide

Warranty card

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(Power adaptor and USB-C charging cable sold separately)

Powerbeats Pro true wireless earbuds

Eartips with four size options

Charging case
Lightning to USB-A charging cable,

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Quick start guide

(USB power adapter sold separately)

beats-powerbeats-pro-2-nike-buds-case-eartips

The Bottom Line 

The Powerbeats Pro 2 Nike Special Edition does not reinvent the category, but it does not need to. What makes this release stand out is the combination of a proven fitness focused earbud platform with one of the most recognizable brands in sports. The design leans hard into that identity with Volt accents and Nike branding, but the real value remains the same: secure fit, long battery life, strong feature set, and the addition of heart rate monitoring that still is not standard across most competitors.

What is missing depends on your priorities. If you are deep into high resolution wireless audio, codec support is limited compared to some rivals, and there is no meaningful shift in sound tuning or hardware from the standard version. This is not an upgrade for existing Powerbeats Pro 2 owners, and it is not trying to be.

Who should consider them is pretty clear. If you want a stable, gym ready earbud with excellent battery life, seamless Apple integration, and a design that actually stays put during real workouts, this makes a lot of sense. The Nike tie in just sharpens the appeal for that audience. Everyone else can still enjoy the feature set, but this one knows exactly who it is for and does not pretend otherwise.

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Pricing & Availability

The Powerbeats Pro 2 – Nike Special Edition is available in Black & Volt for $249.99 USD at Apple.com in the United States and other select markets.

If you prefer,  the Beats Powerbeats Pro 2 is available to order in four colors—Jet Black, Hyper Purple, Quick Sand, and Electric Orange—for $249.99 USD at Apple.com and Amazon 

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AI is transforming nuclear power design and operations to tackle decades of regulatory hurdles and massive construction inefficiencies

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  • AI enables engineers to detect design inconsistencies before construction begins
  • Generative AI automates documentation workflows, creating audit-ready and traceable regulatory applications
  • High-fidelity Digital Twins validate designs virtually and reuse proven engineering patterns

The global energy sector is facing unprecedented demand, yet nuclear power projects continue to encounter extensive delays before construction even begins.

Highly customized engineering, fragmented datasets, and labor-intensive regulatory reviews slow progress across permitting, design, and construction phases.

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TikTok for Business accounts targeted in new phishing campaign

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TikTok for Business accounts targeted in new phishing campaign

Threat actors are targeting TikTok for Business accounts in a phishing campaign that prevents security bots from analyzing malicious pages.

TikTok Business accounts may be targeted due to their high potential for abuse in malvertising campaigns, ad fraud, and the distribution of malicious content.

Browser threat detection and response company Push Security links the campaign to one documented last year, which targeted Google Ad Manager accounts.

TikTok has previously been used to spread information-stealing malware via malicious videos, as well as cryptocurrency scams via fake promotions. TikTok for Business accounts are ideal for such purposes due to their increased reach and perceived legitimacy.

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In a report shared with BleepingComputer, Push Security says that victims are lured to Cloudflare-hosted phishing pages registered on March 24 via NiceNIC, a registrar often reported by cybersecurity researcher for being used for cybercriminal activities.

Push Security could not determine the initial delivery mechanism, but believes that the threat actor uses a similar method as observed in activity reported by Sublime Security.

The initial link redirects via a legitimate Google Storage URL, blocks bots using a Cloudflare Turnstile check, and then redirects to the malicious pages.

The domains feature similar names, and are all hosted on the same Google Storage bucket:

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  • welcome.careerscrews[.]com
  • welcome.careerstaffer[.]com
  • welcome.careersworkflow[.]com
  • welcome.careerstransform[.]com
  • welcome.careersupskill[.]com
  • welcome.careerssuccess[.]com
  • welcome.careersstaffgrid[.]com
  • welcome.careersprogress[.]com
  • welcome.careersgrower[.]com
  • welcome.careersengage[.]com
  • welcome.careerscrews[.]com

The malicious pages impersonate TikTok for Business and Google Careers “Schedule a Call” pages, requesting visitors to enter basic information in a form to validate they’re using a business email address.

Collecting basic information in a first validation step
Collecting basic information in a first validation step
Source: Push Security

After this step, victims are served a fake login page, which is a reverse proxy designed to capture credentials and session cookies, and to exfiltrate them to the attacker.

Since the page acts as an intermediary between the legitimate user and the service, the threat actor can hijack accounts even when the two-factor authentication (2FA) protection is active.

The TikTok themed (top) and Google (bottom) phishing pages
The TikTok themed (top) and Google (bottom) phishing pages
Source: Push Security

Push Security also notes that business account holders often log into TikTok via Google single sign-on (SSO) service. “This means that anyone using Google to login to their TikTok account will effectively have both accounts used to distribute ads compromised in one go.”

Users should be extremely cautious with suspicious invites and job offers, and never trust links sent from unknown contacts. Always check the domain before entering credentials, and use passkeys to protect valuable accounts.

Automated pentesting proves the path exists. BAS proves whether your controls stop it. Most teams run one without the other.

This whitepaper maps six validation surfaces, shows where coverage ends, and provides practitioners with three diagnostic questions for any tool evaluation.

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How Autonomous Drone Warfare Is Emerging in Ukraine

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WHEN KYIV-BORN ENGINEER Yaroslav Azhnyuk thinks about the future, his mind conjures up dystopian images. He talks about “swarms of autonomous drones carrying other autonomous drones to protect them against autonomous drones, which are trying to intercept them, controlled by AI agents overseen by a human general somewhere.” He also imagines flotillas of autonomous submarines, each carrying hundreds of drones, suddenly emerging off the coast of California or Great Britain and discharging their cargoes en masse to the sky.

“How do you protect from that?” he asks as we speak in late December 2025; me at my quiet home office in London, he in Kyiv, which is bracing for another wave of missile attacks.

Azhnyuk is not an alarmist. He cofounded and was formerly CEO of Petcube, a California-based company that uses smart cameras and an app to let pet owners keep an eye on their beloved creatures left alone at home. A self-described “liberal guy who didn’t even receive military training,” Azhnyuk changed his mind about developing military tech in the months following the Russian invasion of Ukraine in February 2022. By 2023, he had relinquished his CEO role at Petcube to do what many Ukrainian technologists have done—to help defend his country against a mightier aggressor.

It took a while for him to figure out what, exactly, he should be doing. He didn’t join the military, but through friends on the front line, he witnessed how, out of desperation, Ukrainian troops turned to off-the-shelf consumer drones to make up for their country’s lack of artillery.

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Ukrainian troops first began using drones for battlefield surveillance, but within a few months they figured out how to strap explosives onto them and turn them into effective, low-cost killing machines. Little did they know they were fomenting a revolution in warfare.

Group observes a drone demonstration indoors, with a presenter explaining features.

Compact black camera module with textured surface and orange ribbon cable on white background.The Ukrainian robotics company The Fourth Law produces an autonomy module [above] that uses optics and AI to guide a drone to its target. Yaroslav Azhnyuk [top, in light shirt], founder and CEO of The Fourth Law, describes a developmental drone with autonomous capabilities to Ukrainian President Volodymyr Zelenskyy and German Chancellor Olaf Scholz.Top: THE PRESIDENTIAL OFFICE OF UKRAINE; Bottom: THE FOURTH LAW

That revolution was on display last month, as the U.S. and Israel went to war with Iran. It soon became clear that attack drones are being extensively used by both sides. Iran, for example, is relying heavily on the Shahed drones that the country invented and that are now also being manufactured in Russia and launched by the thousands every month against Ukraine.

A thorough analysis of the Middle East conflict will take some time to emerge. And so to understand the direction of this new way of war, look to Ukraine, where its next phase—autonomy—is already starting to come into view. Outnumbered by the Russians and facing increasingly sophisticated jamming and spoofing aimed at causing the drones to veer off course or fall out of the sky, Ukrainian technologists realized as early as 2023 that what could really win the war was autonomy. Autonomous operation means a drone isn’t being flown by a remote pilot, and therefore there’s no communications link to that pilot that can be severed or spoofed, rendering the drone useless.

By late 2023, Azhnyuk set out to help make that vision a reality. He founded two companies, The Fourth Law and Odd Systems, the first to develop AI algorithms to help drones overcome jamming during final approach, the second to build thermal cameras to help those drones better sense their surroundings.

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“I moved from making devices that throw treats to dogs to making devices that throw explosives on Russian occupants,” Azhnyuk quips.

Since then, The Fourth Law has dispatched “more than thousands” of autonomy modules to troops in eastern Ukraine (it declines to give a more specific figure), which can be retrofitted on existing drones to take over navigation during the final approach to the target. Azhnyuk says the autonomy modules, worth around US $50, increase the drone-strike success rate by up to four times that of purely operator-controlled drones.

And that is just the beginning. Azhnyuk is one of thousands of developers, including some who relocated from Western countries, who are applying their skills and other resources to advancing the drone technology that is the defining characteristic of the war in Ukraine. This eclectic group of startups and founders includes Eric Schmidt, the former Google CEO, whose company Swift Beat is churning out autonomous drones and modules for Ukrainian forces. The frenetic pace of tech development is helping a scrappy, innovative underdog hold at bay a much larger and better-equipped foe.

All of this development is careening toward AI-based systems that enable drones to navigate by recognizing features in the terrain, lock on to and chase targets without an operator’s guidance, and eventually exchange information with each other through mesh networks, forming self-organizing robotic kamikaze swarms. Such an attack swarm would be commanded by a single operator from a safe distance.

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According to some reports, autonomous swarming technology is also being developed for sea drones. Ukraine has had some notable successes with sea drones, which have reportedly destroyed or damaged around a dozen Russian vessels.

Hand holding a drone with six rotors, outdoors against a blue sky.The Skynode X system, from Auterion, provides a degree of autonomy to a drone.AUTERION

For Ukraine, swarming can solve a major problem that puts the nation at a disadvantage against Russia—the lack of personnel. Autonomy is “the single most impactful defense technology of this century,” says Azhnyuk. “The moment this happens, you shift from a manpower challenge to a production challenge, which is much more manageable,” he adds.

The autonomous warfare future envisioned by Azhnyuk and others is not yet a reality. But Marc Lange, a German defense analyst and business strategist, believes that “an inflection point” is already in view. Beyond it, “things will be so dramatically different,” he says.

“Ukraine pretty rapidly realized that if the operator-to-drone ratio can be shifted from one-to-one to one-to-many, that creates great economies of scale and an amazing cost exchange ratio,” Lange adds. “The moment one operator can launch 100, 50, or even just 20 drones at once, this completely changes the economics of the war.”

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Drones With a View

For a while, jammers that sever the radio links between drones and operators or that spoof GPS receivers were able to provide fairly reliable defense against human-controlled first-person-view attack drones (FPVs). But as autonomous navigation progressed, those electronic shields have gradually become less effective. Defenders must now contend with unjammable drones—ones that are attached to hair-thin optical fibers or that are capable of finding their way to their targets without external guidance. In this emerging struggle, the defenders’ track records aren’t very encouraging: The typical countermeasure is to try to shoot down the attacking drone with a service weapon. It’s rarely successful.

Truck on rural road covered with camouflage netting, trees and fields in the background.A truck outfitted with signal-jamming gear drives under antidrone nets near Oleksandriya, in eastern Ukraine, on 2 October 2025.ED JONES/AFP/GETTY IMAGES

“The attackers gain an immense advantage from unmanned systems,” says Lange. “You can have a drone pop up from anywhere and it can wreak havoc. But from autonomy, they gain even more.”

The self-navigating drones rely on image-recognition algorithms that have been around for over a decade, says Lange. And the mass deployments of drones on Ukrainian battlefields are enabling both Russian and Ukrainian technologists to create huge datasets that improve the training and precision of those AI algorithms.

Six-wheeled robotic vehicle with mounted equipment in a grassy field.A Ukrainian land robot, the Ravlyk, can be outfitted with a machine gun.

While uncrewed aerial vehicles (UAVs) have received the most attention, the Ukrainian military is also deploying dozens of different kinds of drones on land and sea. Ukraine, struggling with the shortage of infantry personnel, began working on replacing a portion of human soldiers with wheeled ground robots in 2024. As of early 2026, thousands of ground robots are crawling across the gray zone along the front line in Eastern Ukraine. Most are used to deliver supplies to the front line or to help evacuate the wounded, but some “killer” ground robots fitted with turrets and remotely controlled machine guns have also been tested.

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In mid-February, Ukrainian authorities released a video of a Ukrainian ground robot using its thermal camera to detect a Russian soldier in the dark of the night and then kill the invader with a round from a heavy machine gun. So far these robots are mostly controlled by a human operator, but the makers of these uncrewed ground vehicles say their systems are capable of basic autonomous operations, such as returning to base when radio connection is lost. The goal is to enable them to swarm so that one operator controls not one, but a whole herd of mesh-connected killer robots.

But Bryan Clark, senior fellow and director of the Center for Defense Concepts and Technology at the Hudson Institute, questions how quickly ground robots’ abilities can progress. “Ground environments are very difficult to navigate in because of the terrain you have to address,” he says. “The line of sight for the sensors on the ground vehicles is really constrained because of terrain, whereas an air vehicle can see everything around it.”

To achieve autonomy, maritime drones, too, will require navigational approaches beyond AI-based image recognition, possibly based on star positions or electronic signals from radios and cell towers that are within reach, says Clark. Such technologies are still being developed or are in a relatively early operational stage.

How the Shaheds Got Better

Russia is not lagging behind. In fact, some analysts believe its autonomous systems may be slightly ahead of Ukraine’s. For a good example of the Russian military’s rapid evolution, they say, consider the long-range Iranian-designed Shahed drones. Since 2022, Russia has been using them to attack Ukrainian cities and other targets hundreds of kilometers from the front line. “At the beginning, Shaheds just had a frame, a motor, and an inertial navigation system,” Oleksii Solntsev, CEO of Ukrainian defense tech startup MaXon Systems, tells me. “They used to be imprecise and pretty stupid. But they are becoming more and more autonomous.” Solntsev founded MaXon Systems in late 2024 to help protect Ukrainian civilians from the growing threat of Shahed raids.

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Silhouette of a triangular drone flying in the sky.A Russian Geran-2 drone, based on the Iranian Shahed-136, flies over Kyiv during an attack on 27 December 2025.SERGEI SUPINSKY/AFP/GETTY IMAGES

First produced in Iran in the 2010s, Shaheds can carry 90-kilogram warheads up to 650 km (50-kg warheads can go twice as far). They cost around $35,000 per unit, compared to a couple of million dollars, at least, for a ballistic missile. The low cost allows Russia to manufacture Shaheds in high quantities, unleashing entire fleets onto Ukrainian cities and infrastructure almost every night.

The early Shaheds were able to reach a preprogrammed location based on satellite-navigation coordinates. Even one of these early models could frequently overcome the jamming of satellite-navigation signals with the help of an onboard inertial navigation unit. This was essentially a dead-reckoning system of accelerators and gyroscopes that estimate the drone’s position from continual measurements of its motions.

Silhouette of person with large equipment under a starry night sky.In the Donetsk Region, on 15 August 2025, a Ukrainian soldier hunts for Shaheds and other drones with a thermalimaging system attached to a ZU23 23-millimeter antiaircraft gun.KOSTYANTYN LIBEROV/LIBKOS/GETTY IMAGES

Ukrainian defense forces learned to down Shaheds with heavy machine guns, but as Russia continued to innovate, the daily onslaughts started to become increasingly effective.

Today’s Shaheds fly faster and higher, and therefore are more difficult to detect and take down. Between January 2024 and August 2025, the number of Shaheds and Shahed-type attack drones launched by Russia into Ukraine per month increased more than tenfold, from 334 to more than 4,000. In 2025, Ukraine found AI-enabling Nvidia chipsets in wreckages of Shaheds, as well as thermal-vision modules capable of locking onto targets at night.

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“Now, they are interconnected, which allows them to exchange information with each other,” Solntsev says. “They also have cameras that allow them to autonomously navigate to objects. Soon they will be able to tell each other to avoid a jammed region or an area where one of them got intercepted.”

These Russian-manufactured Shaheds, which Russian forces call Geran-2s, are thought to be more capable than the garden variety Shahed-136s that Iran has lately been launching against targets throughout the Middle East. Even the relatively primitive Shahed-136s have done considerable damage, according to press accounts.

Those Shahed successes may accrue, at least in part, from the fact that the United States and Israel lack Ukraine’s long experience with fending them off. In just two days in early March, upward of a thousand drones, mostly Shaheds, were launched against U.S. and Israeli targets, with hundreds of them reportedly finding their marks.

One attack, caught on videotape, shows a Shahed destroying a radar dome at the U.S. navy base in Manama, Bahrain. U.S. forces were understood to be attempting to fend off the drones by striking launch platforms, dispatching fighter aircraft to shoot them down, and by using some extremely costly air-defense interceptors, including ones meant to down ballistic missiles. On 4 March, CNN reported that in a congressional briefing the day before, top U.S. defense officials, including Secretary of Defense Pete Hegseth, acknowledged that U.S. air defenses weren’t keeping up with the onslaught of Shahed drones.

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Broken drone on soil, cylindrical container nearby.Russian V2U attack drones are outfitted with Nvidia processors and run computer-vision software and AI algorithms to enable the drones to navigate autonomously.GUR OF THE MINISTRY OF DEFENSE OF UKRAINE

Russia is also starting to field a newer generation of attack drones. One of these, the V2U, has been used to strike targets in the Sumy region of northeastern Ukraine. The V2U drones are outfitted with Nvidia Jetson Orin processors and run computervision software and AI algorithms that allow the drones to navigate even where satellite navigation is jammed.

The sale of Nvidia chips to Russia is banned under U.S. sanctions against the country. However, press reports suggest that the chips are getting to Russia via intermediaries in India.

Antidrone Systems Step Up

MaXon Systems is one of several companies working to fend off the nightly drone onslaught. Within one year, the company developed and battle-tested a Shahed interception system that hints at the sci-fi future envisioned by Azhnyuk. For a system to be capable of reliably defending against autonomous weaponry, it, too, needs to be autonomous.

MaXon’s solution consists of ground turrets scanning the sky with infrared sensors, with additional input from a network of radars that detects approaching Shahed drones at distances of, typically, 12 to 16 km. The turrets fire autonomous fixed-winged interceptor drones, fitted with explosive warheads, toward the approaching Shaheds at speeds of nearly 300 km/h. To boost the chances of successful interception, MaXon is also fielding an airborne anti-Shahed fortification system consisting of helium-filled aerostats hovering above the city that dispatch the interceptors from a higher altitude.

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“We are trying to increase the level of automation of the system compared to existing solutions,” says Solntsev. “We need automatic detection, automatic takeoff, and automatic mid-track guidance so that we can guide the interceptor before it can itself flock the target.”

Gray drone on display stand, surrounded by military personnel in camouflage uniforms.An interceptor drone, part of the U.S. MEROPS defensive system, is tested in Poland on 18 November 2025.WOJTEK RADWANSKI/AFP/GETTY IMAGES

In November 2025, the Ukrainian military announced it had been conducting successful trials of the Merops Shahed drone interceptor system developed by the U.S. startup Project Eagle, another of former Google CEO Eric Schmidt’s Ukraine defense ventures. Like the MaXon gear, the system can operate largely autonomously and has so far downed over 1,000 Shaheds.

What Works in the Lab Doesn’t Necessarily Fly on the Battlefield

Despite the progress on both sides, analysts say that the kind of robotic warfare imagined by Azhnyuk won’t be a reality for years.

“The software for drone collaboration is there,” says Kate Bondar, a former policy advisor for the Ukrainian government and currently a research fellow at the U.S. Center for Strategic and International Studies. “Drones can fly in labs, but in real life, [the forces] are afraid to deploy them because the risk of a mistake is too high,” she adds.

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Two people launching a drone in an open field using a catapult system.Ukrainian soldiers watch a GOR reconnaissance drone take to the sky near Pokrovsk in the Donetsk region, on 10 March 2025.ANDRIY DUBCHAK/FRONTLINER/GETTY IMAGES

In Bondar’s view, powerful AI-equipped drones won’t be deployed in large numbers given the current prices for high-end processors and other advanced components. And, she adds, the more autonomous the system needs to be, the more expensive are the processors and sensors it must have. “For these cheap attack drones that fly only once, you don’t install a high-resolution camera that [has] the resolution for AI to see properly,” she says. “[You install] the cheapest camera. You don’t want expensive chips that can run AI algorithms either. Until we can achieve this balance of technological sophistication, when a system can conduct a mission but at the lowest price possible, it won’t be deployed en masse.”

While existing AI systems are doing a good job recognizing and following large objects like Shaheds or tanks, experts question their ability to reliably distinguish and pursue smaller and more nimble or inconspicuous targets. “When we’re getting into more specific questions, like can it distinguish a Russian soldier from a Ukrainian soldier or at least a soldier from a civilian? The answer is no,” says Bondar. “Also, it’s one thing to track a tank, and it’s another to track infantrymen riding buggies and motorcycles that are moving very fast. That’s really challenging for AI to track and strike precisely.”

Clark, at the Hudson Institute, says that although the AI algorithms used to guide the Russian and Ukrainian drones are “pretty good,” they rely on information provided bysensors that “aren’t good enough.” “You need multiphenomenology sensors that are able to look at infrared and visual and, in some cases, different parts of the infrared spectrum to be able to figure out if something is a decoy or real target,” he says.

German defense analyst Lange agrees that right now, battlefield AI image-recognition systems are too easily fooled. “If you compress reality into a 2D image, a lot of things can be easily camouflaged—like what Russia did recently, when they started drawing birds on the back of their drones,” he says.

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Autonomy Remains Elusive on the Ground and at Sea, Too

To make Ukraine’s emerging uncrewed ground vehicles (UGVs) equally self-sufficient will be an even greater task, in Clark’s view. Still, Bondar expects major advances to materialize within the next several years, even if humans are still going to be part of the decision-making loop.

Military radar equipment in a grassy field.A mobile electronic-warfare system built by PiranhaTech is demonstrated near Kyiv on 21 October 2025.DANYLO ANTONIUK/ANADOLU/GETTY IMAGES

“I think in two or three years, we will have pretty good full autonomy, at least in good weather conditions,” she says, referring to aerial drones in particular. “Humans will still be in the loop for some years, simply because there are so many unpredictable situations when you need an intervention. We won’t be able to fully rely on the machine for at least another 10 or 15 years.”

Ukrainian defenders are apprehensive about that autonomous future. The boom of drone innovation has come hand in hand with the development of sophisticated jamming and radio-frequency detection systems. But a lot of that innovation will become obsolete once the pendulum swings away from human control. Ukrainians got their first taste of dealing with unjammable drones in mid-2024, when Russia began rolling out fiber-optic tethered drones. Now they have to brace for a threat on a much larger scale.

Quadcopter drone flying with a fire extinguisher attached in a cloudy sky.An experimental drone is demonstrated at the Brave1 defense-tech incubator in Kyiv.DANYLO DUBCHAK/FRONTLINER/GETTY IMAGES

“Today, we have a situation where we have lots of signals on the battlefield, but in the near future, in maybe two to five years, UAVs are not going to be sending any signals,” says Oleksandr Barabash, CTO of Falcons, a Ukrainian startup that has developed a smart radio-frequency detection system capable of revealing precise locations of enemy radio sources such as drones, control stations, and jammers.

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Last September, Falcons secured funding from the U.S.-based dual-use tech fund Green Flag Ventures to scale production of its technology and work toward NATO certification. But Barabash admits that its system, like all technologies fielded in Ukrainian war zones, has an expiration date. Instead of radio-frequency detectors, Barabash thinks, the next R&D push needs to focus on passive radar systems capable of identifying small and fast-moving targets based on the signal from sources like TV towers or radio transmitters that propagate through the environment and are reflected by those moving targets. Passive radars have a significant advantage in the war zone, according to Barabash. Since they don’t emit their own signal, they can’t be that easily discovered by the enemy.

“Active radar is emitting signals, so if you are using active radars, you are target No. 1 on the front line,” Barabash says.

Bondar, on the other hand, thinks that the increased onboard compute power needed for AI-controlled drones will, by itself, generate enough electromagnetic radiation to prevent autonomous drones from ever operating completely undetectably.

“You can have full autonomy, but you will still have systems onboard that emit electromagnetic radiation or heat that can be detected,” says Bondar. “Batteries emit electromagnetic radiation, motors emit heat, and [that heat can be] visible in infrared from far away. You just need to have the right sensors to be able to identify it in advance.” She adds that that takeaway is “how capable contemporary detection systems have become and how technically challenging it is to design drones that can reliably operate in the Ukrainian battlefield environment.”

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There Will Be Nowhere to Hide from Autonomous Drones

When autonomous drones become a standard weapon of war, their threat will extend far beyond the battlefields of Ukraine. Autonomous turrets and drone-interceptor fortification might soon dot the perimeter of European cities, particularly in the eastern part of the continent.

Person holding gray drone against a blue sky, preparing to launch it.A fixed-wing drone is tested in Ukraine in April 2025.ANDREWKRAVCHENKO/BLOOMBERG/GETTY IMAGES

Nefarious actors from all over the world have closely watched Ukraine and taken notes, warns Lange. Today, FPV drones are being used by Islamic terrorists in Africa and Mexican drug cartels to fight against local authorities.

When autonomous killing machines become widely available, it’s likely that no city will be safe. “We might see nets above city centers, protecting civilian streets,” Lange says. “In every case, the West needs to start performing similar kinetic-defense development that we see in Ukraine. Very rapid iteration and testing cycles to find solutions.”

Azhnyuk is concerned that the historic defenders of Europe—the United States and the European countries themselves—are falling behind. “We are in danger,” he says. While Russia and Ukraine made major strides in their drones and countermeasures over the past year, “Europe and the United States have progressed, in the best-case scenario, from the winter-of-2022 technology to the summer-of-2022 technology.

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“The gap is getting wider,” he warns. “I think the next few years are very dangerous for the security of Europe.”

This article appears in the April 2026 print issue as “Rise of the AUTONOMOUS Attack Drones.”

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Dublin’s Grand raises $5m pre-seed for ‘real-world’ payment network

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Dublin’s Grand has raised $5m in a pre-seed funding round led by 20VC, with participation from NAP and Firedrop.

Grand describes itself as the “the AI-powered trust network for real-world industries” like construction, manufacturing and trade supply. Now it says the $5m funding round will drive UK expansion and accelerate product development, as it builds its intelligent payment network designed to help businesses evaluate and onboard trade partners with confidence.

Co-founded by payments veterans Kirk Donohoe, Dave Brown and Eamon Doyle, this is the team’s third venture together. They originally worked together at Mastercard Labs and co-founded WhenThen, the payments orchestration platform that was later acquired by Advent International-owned MangoPay in 2023.

“Businesses don’t need another credit score,” said Kirk Donohoe, CEO and co-founder of Grand. “They need always-on intelligence about how their partners actually behave. Poor credit intelligence doesn’t just misprice risk. It misprices opportunity.

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“By applying AI to fragmented and often unstructured data across industries like construction and trade supply, we can move from hindsight to foresight and allow payments and capital to flow based on real trust.”

According to Grand, B2B trade across industries like construction, manufacturing and trade supply exceeds $15trn globally, but the credit decisions that underpin it still rely on fragmented data that is often months or years out of date.

“Creditors make high-stakes calls on outdated snapshots,” Grand said.

It cited the example of the UK, where statutory accounts filed at Companies House can be over a year old by the time they are used, and where over 25,000 company insolvencies were declared in 2023. Unsecured creditors in those failures typically recovered little to nothing, according to Grand.

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Grand Profile, the company’s first product, is designed to show how businesses behave over time, not just how they report, offering a continuous view and flagging early signs of rising risk or improving reliability as they arise.

“Businesses in global trade are making high-stakes decisions – who to partner with, who to pay, who to trust – based on legacy data and processes,” said Kieran Hill, general partner at 20VC.

“Kirk, Dave and Eamon have already built and exited together in payments; they understand the infrastructure layer, and Grand is their most ambitious play yet.”

Already available to UK customers, Grand said it will use this round of funding to grow its engineering and data science teams, expand coverage across European markets, and “deepen the platform’s AI capabilities”.

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