2026-03-11 20:46:21
Feng Qingyang had always hoped to launch his own company, but he never thought this would be how—or that the day would come this fast.
Feng, a 27-year-old software engineer based in Beijing, started tinkering with OpenClaw, a popular new open-source AI tool that can take over a device and autonomously complete tasks for a user, in January. He was immediately hooked, and before long he was helping other curious tech workers with less technical proficiency install the AI agent.
Feng soon realized this could be a lucrative opportunity. By the end of January, he had set up a page on Xianyu, a secondhand shopping site, advertising “OpenClaw installation support.” “No need to know coding or complex terms. Fully remote,” reads the posting. “Anyone can quickly own an AI assistant, available within 30 minutes.”
At the same time, the broader Chinese public was beginning to catch on—and the tool, which had begun as a niche interest among tech workers, started to evolve into a popular sensation.
Feng quickly became inundated with requests, and he started chatting with customers and managing orders late into the night. At the end of February, he quit his job. Now his side gig has now grown into a full-fledged professional operation with over 100 employees. So far, the store has handled 7,000 orders, each worth about 248 RMB or approximately $34.
“Opportunities are always fleeting,” says Feng. “As programmers, we are the first to feel the winds shift.”
Feng is among a small cohort of savvy early adopters turning China’s OpenClaw craze into cash. As users with little technical background want in, a cottage industry of people offering installation services and preconfigured hardware has sprung up to meet them. The sudden rise of these tinkerers and impromptu consultants shows just how eager the general public in China is to adopt cutting-edge AI—even when there are huge security risks.
“Have you raised a lobster yet?”
Xie Manrui, a 36-year-old software engineer in Shenzhen, says he has heard this question nonstop over the past month. “Lobster” is the nickname Chinese users have given to OpenClaw—a reference to its logo.
Xie, like Feng, has been experimenting with OpenClaw since January. He’s built new open-source tools on top of the ecosystem, including one that visualizes the agent’s progress as an animated little desktop worker and another that lets users voice-chat with it.
“I’ve met so many new people through ‘lobster raising,’” says Xie. “Many are lawyers or doctors, with little technical background, but all dedicated to learning new things.”
Lobsters are indeed popping up everywhere in China right now—on and offline. In February, for instance, the entrepreneur and tech influencer Fu Sheng hosted a livestream showing off OpenClaw’s capabilities that got 20,000 views. And just last weekend, Xie attended three different OpenClaw events in Shenzhen, each drawing more than 500 people. These self-organized, unofficial gatherings feature power users, influencers, and sometimes venture capitalists as speakers. The biggest event Xie attended, on March 7, drew more than 1,000 people; in the packed venue, he says, people were shoulder to shoulder, with many attendees unable to even get a seat.
Now China’s AI giants are starting to piggyback on the trend too, promoting their models, APIs, and cloud services (which can be used with OpenClaw), as well as their own OpenClaw-like agents. Earlier this month, Tencent held a public event offering free installation support for OpenClaw, drawing long lines of people waiting for help, including elderly users and children.
This sudden burst in popularity has even prompted local governments to get involved. Earlier this month the government of Longgang, a district in Shenzhen, released several policies to support OpenClaw-related ventures, including free computing credits and cash rewards for standout projects. Other cities, including Wuxi, have begun rolling out similar measures.
These policies only catalyze what’s already in the air. “It was not until my father, who is 77, asked me to help install a ‘lobster’ for him that I realized this thing is truly viral,” says Henry Li, a software engineer based in Beijing.
What’s making this moment particularly lucrative for people with technical skills, like Feng, is that so many people want OpenClaw, but not nearly as many have the capabilities to access it. Setting it up requires a level of technical knowledge most people do not possess, from typing commands into a black terminal window to navigating unfamiliar developer platforms. On the hardware side, an older or budget laptop may struggle to run it smoothly. And if the tool is not installed on a device separate from someone’s everyday computer, or if the data accessible to OpenClaw is not properly partitioned, the user’s privacy could be at risk—opening the door to data leaks and even malicious attacks.
Chris Zhao, known as “Qi Shifu” online, organizes OpenClaw social media groups and events in Beijing. On apps like Rednote and Jike, Zhao routinely shares his thoughts on AI, and he asks other interested users to leave their WeChat ID so he can invite them to a semi-private group chat. The proof required to join is a screenshot that shows your “lobster” up and running. Zhao says that even in group chats for experienced users, hardware and cloud setup remain a constant topic of discussion.
The relatively high bar for setting up OpenClaw has generated a sense of exclusivity, creating a natural opening for a service industry to start unfolding around it. On Chinese e-commerce platforms like Taobao and JD, a simple search for “OpenClaw” now returns hundreds of listings, most of them installation guides and technical support packages aimed at nontechnical users, priced anywhere from 100 to 700 RMB (approximately $15 to $100). At the higher end, many vendors offer to come to help you in person.
Like Feng, most providers of these services are early adopters with some technical ability who are looking for a side gig. But as demand has surged, some have found themselves overwhelmed. Xie, the developer in Shenzhen who created tools to layer on OpenClaw, was asked by a friend who runs one such business to help out over the weekend; the friend had a customer who worked in e-commerce and had little technical experience, so Xie had to show up in person to get it done. He walked away with 600 RMB ($87) for the afternoon.
The growing demand has also pushed vendors like Feng to expand quickly. He has now standardized his operation into tiers: a basic installation, a custom package where users can make specific requests like configuring a preferred chat app, and an ongoing tutoring service for those who want a hand to hold as they find their footing with the technology.
Other vendors in China are making money combining OpenClaw with hardware. Li Gong, a Shenzhen-based seller of refurbished Mac computers, was among the first online sellers to do this—offering Mac minis and MacBooks with OpenClaw preinstalled. Because OpenClaw is designed to operate with deep access to a hard drive and can run continuously in the background unattended, many users prefer to install it on a separate device rather than on the one they use every day. This would help prevent bad actors from infiltrating the program and immediately gaining access to a wide swathe of someone’s personal information. Many turn to secondhand or refurbished options to keep the cost down. Li says that in the last two weeks, orders have increased eightfold.
Though OpenClaw itself is a new technology, the general practice of buying software bundles, downloading third-party packages, and seeking out modified devices is nothing new for many Chinese internet users, says Tianyu Fang, a PhD candidate studying the history of technology at Harvard University. Many users pay for one-off IT support services for tasks from installing Adobe software to jailbreaking a Kindle.
Still, not everyone is getting swept up. Jiang Yunhui, a tech worker based in Ningbo, worries that ordinary users who struggle with setup may not be the right audience for a technology that is still effectively in testing.
“The hype in first-tier cities can be a little overblown,” he says. “The agent is still a proof of concept, and I doubt it would be of any life-changing use to the average person for now.” He argues that using it safely and getting anything meaningful out of it requires a level of technical fluency and independent judgment that most new users simply don’t have yet.
He’s not alone in his concerns. On March 10, the Chinese cybersecurity regulator CNCERT issued a warning about the security and data risks tied to OpenClaw, saying it heightens users’ exposure to data breaches.
Despite the potential pitfalls, though, China’s enthusiasm for OpenClaw doesn’t seem to be slowing.
Feng, now flush with the earnings from his operation, wants to use the momentum—and the capital—to keep building out his own venture with AI tools at the center of it.
“With OpenClaw and other AI agents, I want to see if I can run a one-person company,” he says. “I’m giving myself one year.”
2026-03-11 20:38:00
This is today’s edition of The Download, our weekday newsletter that provides a daily dose of what’s going on in the world of technology.
Pokémon Go was the world’s first augmented-reality megahit. Released in 2016 by Niantic, the AR twist on the juggernaut Pokémon franchise fast became a global phenomenon. “500 million people installed that app in 60 days,” says Brian McClendon, CTO at Niantic Spatial, an AI company that Niantic spun out last year.
Now Niantic Spatial is using that vast trove of crowdsourced data to build a kind of world model—a buzzy new technology that grounds the smarts of LLMs in real environments. The firm wants to use it to help robots navigate more precisely. Read the full story.
—Will Douglas Heaven
In July 2024, after more than three years on Mars, the Perseverance rover came across a peculiar rocky outcrop. Instead of the usual crystals or sedimentary layers, this one had spots. Those specks were the best hint yet of alien life.
NASA began a new mission to bring the rocks back to Earth to study. But now, just over a year and a half later, the project is on life support. As a result, those oh-so-promising rocks may be stuck out there forever.
This also means that, in the race to find evidence of alien life, America has effectively ceded its pole position to its greatest geopolitical rival: China. The superpower is moving full steam ahead with its own version of NASA’s mission.
—Robin George Andrews
This is our latest story to be turned into an MIT Technology Review Narrated podcast, which we’re publishing each week on Spotify and Apple Podcasts. Just navigate to MIT Technology Review Narrated on either platform, and follow us to get all our new content as it’s released.
The must-reads
I’ve combed the internet to find you today’s most fun/important/scary/fascinating stories about technology.
1 Viral AI fakes of the Iran war are flooding X
And Grok is failing to flag them. (Wired $)
+ The conflict could wreak havoc on data centers and electricity costs. (The Verge)
+ Pro-Iran bots are weaponizing posts about Epstein. (Gizmodo)
+ AI is turning the Iran conflict into a show. (MIT Technology Review)
2 Anthropic fears the loss of billions due to the Pentagon’s blacklisting
That’s what the company has told a judge as it seeks to block its designation as a supply-chain risk. (Bloomberg $)
+ Microsoft has backed the company in its legal fight with the Pentagon. (FT $)
+ OpenAI’s “compromise” with the DoD dealt a big blow to Anthropic. (MIT Technology Review)
3 Meta has bought a social network that’s exclusively for bots
Moltbook is a Reddit-like site where AI agents interact with each other. (NYT $)
+ The platform is AI theater. (MIT Technology Review)
4 Ukraine is eagerly offering the US its expertise and tech to counter Iranian drones
Kyiv has sent drones and UAV specialists to military bases in Jordan. (WSJ $)
+ A radio-obsessed civilian is shaping Ukraine’s drone defense. (MIT Technology Review)
5 OnlyFans “chatters” are earning $2 per hour to impersonate models
A worker in the Philippines described the job as “heartbreaking” and “icky.” (BBC)
6 The DHS has removed officials who objected to “illegal” orders about surveillance tech
The officers had refused to mislabel records about the technologies in order to block their release. (Wired)
7 This startup is building data centers run on brain cells
The “biological data centers” are coming to Melbourne and Singapore. (New Scientist $)
8 Anduril is expanding into space defense
The company is buying ExoAnalytic, which specializes in missile defense tracking. (Reuters)
+ We saw a demo of an AI system powering Anduril’s vision for war. (MIT Technology Review)
9 Big tech has a new big idea: AI compute as compensation
Silicon Valley is pitching it as a job perk. (Business Insider)
10 Wordle’s creator is back with a new game
It’s inspired by cryptic crosswords. (The New Yorker $)
Quote of the day
—Bret Schafer, an expert on information manipulation, tells the Washington Post how pro-Iran networks are gaining traction with posts about Epstein.
The quest to figure out farming on Mars
If ever a blade of grass grew on Mars, those days are over. But could they begin again? What would it take to grow plants to feed future astronauts on Mars?
To grow food there, we can’t just drop seeds in the ground and add water. We will need to create a layer of soil that can support life. And to do that, we first have to get rid of the red planet’s toxic salts.
Researchers recently discovered a potential solution—and the early signs are promising. Read the full story.
We can still have nice things
A place for comfort, fun and distraction to brighten up your day. (Got any ideas? Drop me a line)
+ Finally, a rebellion arises against mint’s tyranny over our teeth: Peanut Butter Cup toothpaste.
+ DIY decorators rejoice! The humble paint tray has received an ingeniously simple renovation.
+ Saudi surgeons have successfully separated two conjoined twins.
+ If you’re looking for real innovation, check out British Pie Week’s beef rendang, jerk chicken, and double-size pasties.
2026-03-10 21:47:26
Pokémon Go was the world’s first augmented-reality megahit. Released in 2016 by the Google spinout Niantic, the AR twist on the juggernaut Pokémon franchise fast became a global phenomenon. From Chicago to Oslo to Enoshima, players hit the streets in the urgent hope of catching a Jigglypuff or a Squirtle or (with a huge amount of luck) an ultra-rare Galarian Zapdos hovering just out of reach, superimposed on the everyday world.
In short, we’re talking about a huge number of people pointing their phones at a huge number of buildings. “Five hundred million people installed that app in 60 days,” says Brian McClendon, CTO at Niantic Spatial, an AI company that Niantic spun out in May last year. According to the video-game firm Scopely, which bought Pokémon Go from Niantic at the same time, the game still drew more than 100 million players in 2024, eight years after it launched.
Now Niantic Spatial is using that vast and unparalleled trove of crowdsourced data—images of urban landmarks tagged with super-accurate location markers taken from the phones of hundreds of millions of Pokémon Go players around the world—to build a kind of world model, a buzzy new technology that grounds the smarts of LLMs in real-world environments.
The company’s latest product is a model that it says can pinpoint your location on a map to within a few centimeters, based on a handful of snapshots of the buildings or other landmarks in view. The firm wants to use it to help robots navigate with greater precision in places where GPS is unreliable.
In the first big test of its technology, Niantic Spatial has just teamed up with Coco Robotics, a startup that deploys last-mile delivery robots in a number of cities across the US and Europe. “Everybody thought that AR was the future, that AR glasses were coming,” says McClendon. “And then robots became the audience.”
Coco Robotics deploys around 1,000 flight-case-size robots—built to carry up to eight extra-large pizzas or four grocery bags—in Los Angeles, Chicago, Jersey City, Miami, and Helsinki. According to CEO Zach Rash, the robots have made more than half a million deliveries to date, covering a few million miles in all weather conditions.
But to compete with human couriers, Coco’s robots, which trundle along sidewalks at around five miles per hour, must be as reliable as possible. “The best way we can do our job is by arriving exactly when we told you we were going to arrive,” says Rash. And that means not getting lost.
The problem Coco faces is that it cannot rely on GPS, which can be weak in cities because radio signals bounce off buildings and interfere with each other. “We do deliveries in a lot of dense areas with high-rises and underpasses and freeways, and those are the areas where GPS just never really works,” says Rash.
“The urban canyon is the worst place in the world for GPS,” says McClendon. “If you look at that blue dot on your phone, you’ll often see it drift 50 meters, which puts you on a different block going a different direction on the wrong side of the street.” That’s where Niantic Spatial comes in.
For the last few years, Niantic Spatial has been taking the data collected from players of Pokémon Go and Ingress (Niantic’s previous phone-based AR game, launched in 2013) and building a visual positioning system, technology that tells you where you are based on what you can see. “It turns out that getting Pikachu to realistically run around and getting Coco’s robot to safely and accurately move through the world is actually the same problem,” says John Hanke, CEO of Niantic Spatial.
“Visual positioning is not a very new technology,” says Konrad Wenzel at ESRI, a company that develops digital mapping and geospatial analysis software. “But it’s obvious that the more cameras we have out there, the better it becomes.”
Niantic Spatial has trained its model on 30 billion images captured in urban environments. In particular, the images are clustered around hot spots—places that served as important locations in Niantic’s games that players were encouraged to visit, such as Pokémon battle arenas. “We had a million-plus locations around the world where we can locate you precisely,” says McClendon. “We know where you’re standing within several centimeters of accuracy and, most importantly, where you’re looking.”
The upshot is that for each of those million locations, Niantic Spatial has many thousands of images taken in more or less the same place but from different angles, at different times of day, and in different weather conditions. Each of those images comes with detailed metadata that pinpoints where in space the phone was at the time it captured the image, including which way the phone was facing, which way up it was, whether or not it was moving, how fast and in which direction, and more.
The firm has used this data set to train a model to predict exactly where it is by taking into account what it is looking at—even for locations other than those million hot spots, where good sources of image and location data are scarcer.
In addition to GPS, Coco’s robots, which are fitted with four cameras, will now use this model to try to figure out where they are and where they are headed. The robots’ cameras are hip-height and point in all directions at once, so their viewpoint is a little different from a Pokémon Go player’s, but adapting the data was straightforward, says Rash.
Rival companies use visual positioning systems too. For example, Starship Technologies, a robot delivery firm founded in Estonia in 2014, says its robots use their sensors to build a 3D map of their surroundings, plotting the edges of buildings and the position of streetlights.
But Rash is betting that Niantic Spatial’s tech will give Coco an edge. He claims it will allow his robots to position themselves in the correct pickup spots outside restaurants, making sure they don’t get in anybody’s way, and stop just outside the customer’s door instead of a few steps away, which might have happened in the past.
When Niantic Spatial started work on its visual positioning system, the idea was to apply it to augmented reality, says Hanke. “If you are wearing AR glasses and you want the world to lock in to where you’re looking, then you need some method for doing that,” he says. “But now we’re seeing a Cambrian explosion in robotics.”
Some of those robots may need to share spaces with humans—spaces such as construction sites and sidewalks. “If robots are ever going to assimilate into that environment in a way that’s not disruptive for human beings, they’re going to have to have a similar level of spatial understanding,” says Hanke. “We can help robots find exactly where they are when they’ve been jostled and bumped.”
The Coco Robotics partnership is the start. What Niantic Spatial is putting in place, says Hanke, are the first pieces of what he calls a living map: a hyper-detailed virtual simulation of the world that changes as the world changes. As robots from Coco and other firms move about the world, they will provide new sources of map data, feeding into more and more detailed digital replicas of the world.
But the way Hanke and McClendon see it, maps are not only becoming more detailed; they are being used more and more by machines. That shifts what maps are for. Maps have long been used to help people locate themselves in the world. As they moved from 2D to 3D to 4D (think of real-time simulations, such as digital twins), the basic principle hasn’t changed: Points on the map correspond to points in space or time.
And yet maps for machines may need to become more like guidebooks, full of information that humans take for granted. Companies like Niantic Spatial and ESRI want to add descriptions that tell machines what they’re actually looking at, with every object tagged with a list of its properties. “This era is about building useful descriptions of the world for machines to comprehend,” says Hanke. “The data that we have is a great starting point in terms of building up an understanding of how the connective tissue of the world works.”
There is a lot of buzz about world models right now—and Niantic Spatial knows it. LLMs may seem like know-it-alls, but they have very little common sense when it comes to interpreting and interacting with everyday environments. World models aim to fix that. Some firms, such as Google DeepMind and World Labs, are developing models that generate virtual fantasy worlds on the fly, which can then be used as training dojos for AI agents.
Niantic Spatial says it is coming at the problem from a different angle. Push map-making far enough and you’ll end up capturing everything, says McClendon: “We’re not there yet, but we want to be there. I’m very focused on trying to re-create the real world.”
2026-03-10 21:00:00
Loudoun County, Virginia, once known for its pastoral scenery and proximity to Washington, DC, has earned a more modern reputation in recent years: The area has the highest concentration of data centers on the planet.
Ten years ago, these facilities powered email and e-commerce. Today, thanks to the meteoric rise in demand for AI-infused everything, local utility Dominion Energy is working hard to keep pace with surging power demands. The pressure is so acute that Dulles International Airport is constructing the largest airport solar installation in the country, a highly visible bid to bolster the region’s power mix.
Data center campuses like Loudoun’s are cropping up across the country to accommodate an insatiable appetite for AI. But this buildout comes at an enormous cost. In the US alone, data centers consumed roughly 4% of national electricity in 2024. Projections suggest that figure could stretch to 12% by 2028. To put this in perspective, a single 100-megawatt data center consumes roughly as much electricity as 80,000 American homes. Data centers being built today are gearing up for gigawatt scale, enough to power a mid-sized city.
For enterprise leaders, energy costs associated with AI and data infrastructure are quickly becoming both a budget concern and a potential bottleneck on growth. Meeting this moment calls for a capability most organizations are only beginning to develop: energy intelligence. The emerging discipline refers to understanding where, when, and why energy is consumed, and using that insight to optimize operations and control costs.
These efforts stand to address both immediate financial pressures and longer-term reputational risks, as communities like Loudoun County grow increasingly concerned about the energy demands associated with nearby data center development.
In December 2025, MIT Technology Review Insights conducted a survey of 300 executives to understand how companies are thinking about energy intelligence today, as well as where they’re anticipating challenges in the future.
Here are five of our most notable findings:
This content was produced by Insights, the custom content arm of MIT Technology Review. It was not written by MIT Technology Review’s editorial staff. It was researched, designed, and written by human writers, editors, analysts, and illustrators. This includes the writing of surveys and collection of data for surveys. AI tools that may have been used were limited to secondary production processes that passed thorough human review.
2026-03-10 20:55:32
This is today’s edition of The Download, our weekday newsletter that provides a daily dose of what’s going on in the world of technology.
Much of the spotlight on AI in the Iran conflict has focused on models like Claude helping the US military decide where to strike. But a wave of “vibe-coded” intelligence dashboards—and the ecosystem surrounding them—reflect a new role that AI is playing in wartime: mediating information, often for the worse.
These sorts of intelligence tools have much promise. Yet there are real reasons to be suspicious of their data feeds. Read the full story.
—James O’Donnell
This story is from The Algorithm, our weekly newsletter on AI. Sign up to receive it in your inbox every Monday.
The must-reads
I’ve combed the internet to find you today’s most fun/important/scary/fascinating stories about technology.
1 Anthropic has sued the US government
The AI firm wants to stop the Pentagon from blacklisting it. (Reuters)
+ The White House is preparing a new executive order to weed out the company’s technology. (Axios)
+ Defense experts are alarmed. (CNBC)
+.Google and OpenAI staff have filed a legal brief backing Anthropic against Trump. (Wired $)
+ The company’s stance won many supporters. (MIT Technology Review)
2 GPS jamming has become a crucial battleground in the Middle East
The interference is endangering—and protecting—ships and planes. (BBC)
+ Signal jamming has made navigating the Strait of Hormuz even more difficult. (Bloomberg)
+ Quantum navigation offers a potential solution. (MIT Technology Review)
3 A tech journalist found his AI clone editing for Grammarly
It’s providing AI-generated feedback “inspired by” real writers without their consent. (Platformer)
+ Could ChatGPT do the jobs of journalists and copywriters? (MIT Technology Review)
4 Nvidia plans to launch an open-source platform for AI agents
It’s already pitching the “NemoClaw” product to enterprise software firms. (Wired $)
+ But don’t let the AI agents hype get ahead of reality (MIT Technology Review)
5 A startup wants to launch a space mirror that reflects sunlight onto Earth
Reflect Orbital reckons it could power solar panels at night. Scientists are appalled. (NYT)
6 Yann LeCun’s AI startup has raised over $1bn in Europe’s largest seed round
Meta’s former chief AI scientist plans to build systems that “understand the world.” (Bloomberg)
7 Hinge’s CEO insists the app doesn’t rate users’ attractiveness
Jackie Jantos’ strategy has helped Hinge defy the decline in dating apps. (FT $)
+ AI companions are stealing hearts—and it’s getting weird. (New Yorker $)
+ It’s surprisingly easy to fall into a relationship with a chatbot. (MIT Technology Review)
8 “AI psychosis” could be afflicting your loved ones
If so, here’s how you can help them. (404 Media)
+ One solution: AI should be able to “hang up” on you. (MIT Technology Review)
9 Nintendo is suing Trump over illegal tariffs
The gaming giant has joined a lawsuit seeking over $200 billion in refunds. (Ars Technica)
10 Bio-tech is turning ancient poop into a map of lost civilizations
Molecular sensors are finding human traces where physical ruins have vanished. (Nature)
Quote of the day
—Yann LeCun gives Wired his take on the Anthropic’s spat the Pentagon.
This giant microwave may change the future of war
armed forces are hunting for a weapon that disables drones en masse—and they want it fast.
One solution focuses on microwaves: high-powered electronic devices that push out kilowatts of power to zap the circuits of a drone as if it were the tinfoil you forgot to take off your leftovers when you heated them up.
Defense tech startup Epirus may have the winning formula. The company has developed a cutting-edge, cost-efficient drone zapper that’s sparking the interest of the US military. And drones are just one of its targets. Read the full story.
—Sam Dean
We can still have nice things
A place for comfort, fun and distraction to brighten up your day. (Got any ideas? Drop me a line.)
+ Werner Herzog’s magnificent movie about Africa’s ghost elephants has arrived on Disney+ and Hulu.
+ A “city killer” asteroid won’t hit Earth after all. Phew.
+ The Met is publishing high-definition 3D scans of over 100 iconic works.
+ Marty and Doc from Back to the Future are still BFFs in real life.
2026-03-09 23:11:01
This story originally appeared in The Algorithm, our weekly newsletter on AI. To get stories like this in your inbox first, sign up here.
“Anyone wanna host a get together in SF and pull this up on a 100 inch TV?”
The author of that post on X was referring to an online intelligence dashboard following the US-Israel strikes against Iran in real time. Built by two people from the venture capital firm Andreessen Horowitz, it combines open-source data like satellite imagery and ship tracking with a chat function, news feeds, and links to prediction markets, where people can bet on things like who Iran’s next “supreme leader” will be (the recent selection of Mojtaba Khamenei left some bettors with a payout).
I’ve reviewed over a dozen other dashboards like this in the last week. Many were apparently “vibe-coded” in a couple of days with the help of AI tools, including one that got the attention of a founder of the intelligence giant Palantir, the platform through which the US military is accessing AI models like Claude during the war. Some were built before the conflict in Iran, but nearly all of them are being advertised by their creators as a way to beat the slow and ineffective media by getting straight to the truth of what’s happening on the ground. “Just learned more in 30 seconds watching this map than reading or watching any major news network,” one commenter wrote on LinkedIn, responding to a visualization of Iran’s airspace being shut down before the strikes.
Much of the spotlight on AI and the Iran conflict has rightfully been on the role that models like Claude might be playing in helping the US military make decisions about where to strike. But these intelligence dashboards and the ecosystem surrounding them reflect a new role that AI is playing in wartime: mediating information, often for the worse.
There’s a confluence of factors at play. AI coding tools mean people don’t need much technical skill to assemble open-source intelligence anymore, and chatbots can offer fast, if dubious, analysis of it. The rise in fake content leaves observers of the war wanting the sort of raw, accurate analysis normally accessible only to intelligence agencies. Demand for these dashboards is also driven by real-time prediction markets that promise financial rewards to anyone sufficiently informed. And the fact that the US military is using Anthropic’s Claude in the conflict (despite its designation as a supply chain risk) has signaled to observers that AI is the intelligence tool the pros use. Together, these trends are creating a new kind of AI-enabled wartime circus that can distort the flow of information as much as it clarifies it.
As a journalist, I believe these sorts of intelligence tools have a lot of promise. While many of us know that real-time data on shipping routes or power outages exist, it’s a powerful thing to actually see it all assembled in one place (though using it to watch a war unfold while you munch on popcorn and place bets turns the war into perverse entertainment). But there are real reasons to think that these sorts of raw data feeds are not as informative as they may feel.
Craig Silverman, a digital investigations expert who teaches investigative techniques, has been keeping a log of these dashboards (he’s up to 20). “The concern,” he says, “is there’s an illusion of being on top of things and being in control, where all you’re really doing is just pulling in a ton of signals and not necessarily understanding what you’re seeing, or being able to pull out true insights from it.”
One problem has to do with the quality of the information. Many dashboards feature “intel feeds” with AI-generated summaries of complex, ever-changing news events. These can introduce inaccuracies. By design, the data is not especially curated. Instead, the feeds just display everything at once, with a map of strike locations in Iran next to the prices of obscure cryptocurrencies.
Intelligence agencies, on the other hand, pair data feeds with people who can offer expertise and historical context. They also, of course, have access to proprietary information that doesn’t show up on the open web.
The implicit promise from the people building and selling this sort of information pipeline about the Iran conflict is that AI can be a great democratizing force. There’s a secret feed of information that only the elites have had access to, the thinking goes, but now AI can bring it to everyone to do with what they wish, whether that’s simply to be more informed or to make bets on nuclear strikes. But an abundance of information, which AI is undeniably good at assembling, does not come with the accuracy or context required for real understanding. Intelligence agencies do this in-house; good journalism does the same work for the rest of us.
It is, by the way, hard to overstate the connection this all has with betting markets. The dashboard created by the pair at Andreessen Horowitz has a scrolling list of bets being made on the prediction platform Kalshi (which Andreessen Horowitz has invested in). Other dashboards link to Polymarket, offering bets on whether the US will strike Iraq or when Iran’s internet will return.
AI has also long made it cheaper and easier to spread fake content, and that problem is on full display during the Iran conflict: last week the Financial Times found a slew of AI-generated satellite imagery spreading online.
“The emergence of manipulated or outright fake satellite imagery is really concerning,” Silverman says. The average person tends to see such imagery as very trustworthy. The spread of such fakes could erode confidence in one of the most important pieces of evidence used to show what’s actually happening in the war.
The result is an ocean of AI-enabled content—dashboards, betting markets, photos both real and fake—that makes this war harder, not easier, to comprehend.
