Tag: technology

How Flock Cameras Wrongly Tracked Me for Days Over ‘Stolen’ Plates and Sent Police After Me

Are you armed?!” the police officer screamed. “Get out of the car!”

On an otherwise normal Sunday afternoon in late June, I’d decided to take the $155,000 Range Rover I was testing that week out to run some errands with my wife. Little did I know that choice would complete a technological chain linking surveillance cameras, AI, and law enforcement that led to me and my wife being surrounded by police, hands on their guns, in a Kohl’s parking lot in suburban Minnesota.

After dropping off our Amazon returns, we’d just gotten back in the Range Rover and reversed maybe two feet out of the spot when four cop cars came flying out of nowhere and boxed us in. The officers jumped out and started shouting. It’s a situation that can quickly and frequently turn bad, so as unprepared as I was, I followed their orders, got out with my hands up, and tried to figure out what the hell was happening.

Eventually, after a tense hour, I did. The Plymouth Police Department had been tracking me for days using Flock license plate cameras, waiting for the right moment to strike, because they thought I’d stolen the Range Rover. And the reason I was ID’d as a dangerous car thief was a simple data error made 2,000 miles away in California, creating an edge case within an edge case that Flock’s AI camera network was unable to handle.

We now live in a surveillance state where cameras mounted on stoplights are tracking our cars, our devices, our pets, and even us. This is just the beginning; next, these cameras could be put in motion using our kids’ school buses. Whether you’ve actually stolen a car or are just rolling down the road having done nothing wrong, like me, once these systems have you in their crosshairs, there’s pretty much only one way it can go. Welcome to the future. It’s scary out there.

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The Drone Has Replaced the Tank

Military strategists are still fighting the last war while the battlefield has already changed. Every major conflict throughout history has been defined by a technological revolution. Gunpowder ended the age of castles. Tanks transformed World War II. Precision missiles reshaped modern warfare. Now we have entered the age of the drone. The military that cannot dominate the skies with unmanned systems will lose, regardless of how many tanks, aircraft, or soldiers it possesses.

South Korea has reached the same conclusion. Its Defense Ministry announced that it will train approximately 500,000 soldiers, sailors, airmen, and marines as “drone warriors.” Defense Minister Ahn Gyu-back said every service member should become as proficient with drones as they are with their personal weapons. The plan calls for procuring 11,000 commercial drones by the end of 2026, expanding to 60,000 training drones by 2029, while also acquiring more than 20,000 low-cost combat drones by 2030. Seoul is accelerating production of loitering munitions, AI-enabled drone swarms, laser weapons, and microwave systems designed to destroy incoming drones.

They are responding to the lessons of Ukraine, where inexpensive FPV drones costing only hundreds or thousands of dollars routinely destroy tanks worth millions. The battlefield has become saturated with unmanned aircraft. Ukraine plans to manufacture roughly 7 million military drones in 2026 after producing about 4 million in 2025. According to Ukrainian officials, drones now account for the overwhelming majority of battlefield strikes, fundamentally changing military doctrine. Entire branches of both the Ukrainian and Russian militaries are now dedicated solely to unmanned systems.

A modern drone operator can eliminate armor, artillery, supply convoys, or individual soldiers from miles away while sitting in relative safety. Fiber-optic drones have largely defeated electronic jamming. AI-assisted targeting is reducing operator workload. Swarm attacks can overwhelm traditional air defenses that were designed to intercept aircraft, not hundreds of inexpensive autonomous systems arriving simultaneously. Ukraine has even developed interceptor drones whose sole mission is to hunt other drones, creating an entirely new layer of aerial combat.

South Korea is not alone. Russia formally established its Unmanned Systems Forces, with Ukrainian military estimates claiming the branch could expand from roughly 80,000 personnel today to more than 165,000 during 2026 and perhaps over 200,000 by 2030. NATO countries are pouring billions into drone production, counter-drone technologies, autonomous weapons, and electronic warfare. The United States, China, Israel, Turkey, and Europe are all racing to build domestic drone industries because they understand the next war will not be won by the side with the largest army. It will be won by the side that can produce, replace, and innovate faster than its opponent.

This is precisely why I have warned that the War Cycle is changing the global economy. Wars no longer require decades to build fleets of battleships or thousands of heavy tanks. A nation with sufficient manufacturing capacity can produce tens of thousands of drones every month. The barriers to entry have collapsed. Software updates now matter as much as ammunition. Engineers have become as important as infantry.

The defense industry is no longer limited to traditional contractors producing aircraft carriers and fighter jets. Semiconductor manufacturers, AI companies, battery producers, optics firms, communications specialists, robotics companies, and rare-earth miners have all become part of the defense sector. This is why governments are scrambling to secure critical minerals, expand chip production, and protect supply chains. They are preparing for a world where industrial capacity determines military survival.

Our computer has consistently projected that 2026 marks the acceleration of the international War Cycle. The military transformation unfolding before our eyes confirms that forecast. The next great conflict will not resemble Iraq, Afghanistan, or even the opening stages of Ukraine. It will be fought by autonomous systems, artificial intelligence, electronic warfare, and millions of inexpensive drones operating continuously across every battlefield. The drone has become what the machine gun was in World War I and what the tank became in World War II. Anyone who fails to recognize that reality is preparing for a war that no longer exists.

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Deadly bacteria found in major US city’s wastewater system tied to Mark Zuckerberg’s $800m data center

Meta‘s massive AI data center in Wyoming is facing scrutiny after an unexpected contamination incident emerged during construction.

The Mark Zuckerberg-owned company is developing a 715,000sq ft campus in Cheyenne that is set to go online next year, but its contractor has come under fire after city officials traced wastewater containing a rare bacterium to the project.

Known as Cupriavidus gilardii, the naturally occurring bacterium is typically found in soil and water. While harmless to most healthy people, it can cause severe pneumonia, bloodstream and lung infections, and, in rare cases, death among people with weakened immune systems. 

Cheyenne’s Board of Public Utilities (BOPU) said the bacterium was found in wastewater discharged by Goat Systems, a contractor working on Meta’s $800 million data center. 

According to the BOPU, the bacterium was first detected during routine wastewater sampling in late February, but was only announced last Thursday.

Meta said its general contractor, Fortis, began hauling industrial wastewater offsite and that independent testing found no trace of the substance to date.

Officials stressed that it did not contaminate the city’s drinking water, but said it disrupted the municipal reclaimed water system and required months of cleanup. 

However, the city permanently revoked Meta’s authorization to discharge wastewater from its fill-and-flush operations into Cheyenne’s treatment system, where the water is recycled and later used to irrigate parks and other public spaces. 

A Meta spokesman told the Daily Mail: ‘When the board shared that it found a substance in the city’s wastewater – not public drinking water – Fortis immediately stopped discharging industrial wastewater and began hauling it offsite.

‘Fortis also began its own water testing with an independent environmental specialist, which has found no trace of the substance. 

‘Meta is committed to being a good neighbor in Cheyenne, including through the protection of local water resources, and will continue encouraging collaboration between Fortis and the board until this situation is resolved.’

It comes as AI data centers face mounting scrutiny across the US for their enormous demands on local water and power supplies. 

According to Data Center Map, there are nearly 4,500 data centers nationwide, with some facilities consuming as much as 300,000 gallons of water a day, roughly the same amount used by 1,000 households.

Goat Systems LLC is the corporate entity Meta uses for the construction of the center, dubbed Project Cosmo.

Officials said the contaminated wastewater was discharged during a fill-and-flush process used to prepare the data center’s cooling system before it goes online. 

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Surveillance Disguised as Safety: Cars Sold in EU To Spy on Drivers 24/7

As of Tuesday, July 7th, all new cars sold within the European Union are required by law to include an extra spy gadget, whether you want it or not. 

The so-called driver monitoring camera, switched on at all times while the car is running above 20 km/h, and capable of precisely tracking the driver’s eye movements, is part of the now mandatory Advanced Driver Distraction Warning system, or ADDW. 

Its purpose is to detect if the driver falls asleep or gets distracted, and if they look away from the road for a certain amount of time, depending on the speed, the car warns them with a combination of sound, light, or vibration. 

The tech must also be so advanced as to know exactly if the driver is looking at the speedometer or the display screen, for instance, each with its own allowed number of seconds before the system activates. Looking at a phone or turning back to the kids, however, earns an instant warning.

BREAKING:

The EU today introduced the new requirement for all new cars registered in Europe to have installed cameras filming the driver’s face.

The system is called Advanced Driver Distraction Warning, ADDW, and is part of the EU’s General Safety Regulation.

The camera tracks… pic.twitter.com/oqnWXuz0ir— Visegrád 24 (@visegrad24) July 7, 2026

The idea may be a noble one, as the EU estimated that the new measure will save 25,000 lives by 2038. However, it’s also problematic on multiple fronts. 

Not only is it the latest annoying piece of EU overregulation—tests indicate that the system activates way too often, confuses blinking with drowsiness, and tends to tell drivers to take a break even if they’ve been driving for ten minutes—but the regulation leaves room for plenty of privacy concerns.

On paper, the ADDW should work on a “closed loop” system, meaning all data is processed locally, within the car, and no footage should be uploaded to any third-party server, be it the car manufacturer’s or law enforcement’s. 

However, data privacy experts warned that the implementation might not be so straightforward. 

For one, the EU regulation does not impose any independent audit to ensure that the ADDW systems installed actually operate on a closed-loop basis. Meaning both the car manufacturers and the tech companies selling them these systems could theoretically circumvent the rules and stealthily collect data on drivers.

Secondly, the EU offers little clarity over how the data is handled. We don’t know how much footage the system captures once a “distraction” decision has been made, nor how long that data is stored or when it gets deleted, if it ever does. 

The implications are obvious. The continuous surveillance of the inside of a car can net car companies (or any third party that’s capable of hacking into it) a treasure trove of data that’s too valuable to pass on. Put simply, driver behavior can be turned into precious consumer data to be used internally or sold to the highest bidder.

And this is not just a hypothetical, but something that already happened. In 2024, GM, Honda, Acura, Kia, Hyundai, and Mitsubishi were all caught sharing driver behavior data—including mileage, speed, hard braking, and rapid acceleration—with multiple data brokers. These turned the data into “risk scores” and sold them to insurance companies, which then freely used them to increase their personalized rates by over 20%.

Another investigation in 2023 revealed that Tesla employees had been secretly pulling and sharing video footage made by the forward-facing cameras of their cars, including clips of crashes, road-rage incidents, and even of people getting undressed near their vehicles. 

Now imagine what could go wrong when suddenly millions of European cars all have cameras facing inside. Even if GDPR should protect consumers on paper, it’s only a matter of time until someone gains access to all the sensitive data and footage these cameras capture along the way.

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Current State Of Physical AI: Everything You Need To Know

Citi’s Robotics & Physical AI Leadership Conference wrapped up on Tuesday. The annual Citi Research event brings together robotics founders, investors, operators, and industry executives to assess the state of “physical AI.”

Analyst Heath Terry summarized the key takeaways Wednesday morning, painting a picture of the robotics industry moving from proof of concept to commercial deployment, while warning that scaling robots remains challenging.

“Labor shortages, reshoring, and favorable regulatory tailwinds are accelerating enterprise demand, while data scarcity, talent constraints, battery limitations, and high deployment costs remain key friction points,” Terry explained to clients. 

Citi said the winners in physical AI will likely be firms that own proprietary real-world data, solve specific labor bottlenecks and use Robotics-as-a-Service models to reduce upfront costs for customers.

Terry highlighted automation-exposed industrial names including Rockwell Automation, Emerson Electric, Honeywell, Symbotic, Ralliant and Belden as potential beneficiaries.

Humanoids are attracting significant investor interest. Last month, we detailed how readers can invest ahead of a major ramp in humanoid production expected in the coming quarters. Read the report. 

Over the last two years, about $20 billion has been invested in physical AI, with applications spanning warehouses, logistics, trucking, construction, aviation, and defense.

Last week, carmaker BMW revealed that a new upgraded humanoid is walking its factory floors at the Spartanburg plant in South Carolina. 

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Waymo Robotaxi “Snitches” On Two 15-Year-Olds Drinking & Shooting Orbeez Guns In Bay Area

Two 15-year-old boys were detained in San Mateo Monday afternoon after the Waymo robotaxi they were riding in reported them to police – for drinking alcohol and firing a gel-bead blaster out of the moving car – then pulled itself over so officers could collect them.

Waymo’s remote monitors spotted the behavior on the vehicle’s interior cameras and called the San Mateo Police Department around 2:10 p.m. with the car’s exact location. The company then disabled the vehicle near 20th Avenue and El Camino Real, telling the pair the car was having trouble – a ruse that bought officers time to get into position.

Because the initial report described what looked like a real firearm, police conducted a high-risk stop, approaching with guns drawn and a police dog deployed. No one was hurt. Inside, officers found an Orbeez-style gel blaster – painted over to pass for the real thing – and open alcohol.

The teens cooperated, were detained, and were released to their parents. The case has been forwarded to the San Mateo County District Attorney’s office for review of possible charges, including underage drinking, and police say they plan to pull the Waymo’s interior video.

“Parents do you know where your teens are? @waymo does!” The department wrote on Facebook: “After calling us and stopping the car, we were able to safely remove both subjects and determined they were shooting Orbeez from the car as they sipped on afternoon libations while being chauffeured around town in the driverless vehicle.”

“While there was some ingenuity to this scheme, toy guns, water guns, and BB guns all pose real dangers, especially to an untrained eye… Shooting projectiles at speed can cause real damage. And lest not forget the underage drinking. All bad ideas today for these two. Well, the Waymo might have been the smartest idea yet, because driving impaired would’ve made this so much worse.”

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Risk and AI: It’s Tricky

A funny thing happens on the way to understanding risk: we discover it’s tricky. We think we see all the risks, and think we can mitigate or hedge those risks, but by its very nature, risk evades such simplistic filters and metrics. Risk remains hidden, offscreen, invisible, building up out of sight, awaiting a catalyst that’s equally undetectable until it manifests, and after the fact, we look back and ask, why didn’t we see that coming?

Risk is tricky like that. It can lay dormant for decades and then erupt with little warning.

Risk is tricky in other ways. In our hubris, we see the power and might of our technologies, systems and foresight, and reckon these are so robust they will easily survive any tectonic shift, as we’ve planned for emergencies.

But our faith in the might of our civilization is itself a source of risk because the risk of Model Collapse–the breakdown not of a supply chain or technology but of our entire conceptual construct of how the world works–goes unrecognized because our confidence that our model maps the real world is so high that we are incapable of recognizing its drift into hallucination and civilizational psychosis.

In other words, our confidence that our conceptual mythologies are accurately mapping the real world is itself a source of civilizational risk because this confidence makes it inevitable that we do more of what’s failing, as the alternative–recognizing our conceptual models and mythologies are self-serving rationalizations that substitute artifice for realistic appraisals–is conceptually and emotionally impossible.

Put another way: Emperor Norton’s delusions of power and grandeur were harmless as long as he was recognized as delusional. But should Emperor Norton actually be given the power he believed was his to wield, then risk rises accordingly.

Consider the bet being made globally that the current iteration of AI will be 1) immensely profitable (the most important thing in the Universe) and 2) immensely productive (secondary to immensely profitable but necessary as a motivation for everyone to throw trillions of dollars at purveyors of AI). The risk that this bet–and the assumptions that make it not only rational but pressing–is the equivalent of handing Emperor Norton the keys to the kingdom with little evidence he will be a wise leader, is unimaginable in the current model / mythology, and so therefore it doesn’t exist.

The worst that could possibly happen in the current model / mythology is a brief spot of bother in the stock market as euphoric overvaluations come down to Earth, and then the immense profits start flowing and markets rocket higher in a multi-decade Bull Market of AI Productivity.

The possibility that the current iteration of AI is innately incapable of metaphorically boiling away the seas is not on the screen, any more than a stock market crash or social upheaval is on the screen. Yet if the fantasy of vast, unstoppable floods of profits driven by vast increases in productivity fail to materialize on a very short timeline, then both a stock market crash and social upheaval move from “impossible” straight through “unlikely” to “happening now,” leaving everyone who thought they understood risk and were properly hedged against unwelcome change in a state of disbelief and wonderment.

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Air Force Engineer Accused Of Cutting Down AI Cameras Becomes Unlikely Hero, Raises Thousands For Legal Defense

A U.S. Air Force engineer charged with allegedly destroying a series of AI-powered license plate surveillance cameras has become an unlikely cause célèbre among privacy advocates, drawing thousands of dollars in donations to help fund his legal defense, according to Yahoo News.

Jeffrey Sovern, a 41-year-old Air Force engineer and mechanic from Virginia, is accused of cutting down multiple Flock Safety license plate reader cameras. He now faces 13 counts of destruction of property, along with six counts each of petit larceny and possession of burglary tools.

The case comes as Flock Safety’s automated license plate reader network continues to spread rapidly across the country. Supporters say the cameras help police solve crimes, while critics argue they create a growing surveillance network that tracks the movements of ordinary Americans and raises serious privacy concerns.

Yahoo News writes that opposition to the systems has intensified in some communities, with vandals reportedly using everything from spray paint and garbage bags to chainsaws to disable or destroy the cameras.

Sovern has made no secret of his views. In a GoFundMe campaign created to cover his legal expenses, he framed the case as a fight over privacy rights.

“My name is Jeff and I appreciate my privacy. I appreciate everyone’s right to privacy, enshrined in the fourth amendment,” Sovern wrote.

He said the criminal case has taken a significant emotional toll on him and those close to him, adding that the encouragement he has received online prompted him to launch the fundraiser.

Originally seeking $8,500, the campaign has gained momentum as news of the case has spread. It has now brought in more than $15,000 from over 400 contributors, far surpassing its initial goal.

In a recent update following a preliminary hearing, Sovern thanked supporters for helping bring attention to the issue.

“Thank you to those that had the time to show support this week!” he wrote. “We have seen a huge uptick in awareness of the system and this case.”

He also urged supporters to continue advocating against what he called an expanding surveillance network, encouraging people to “reach out to the local governments and demand that these systems are taken down.”

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Zuckerberg to spend over $10B on “historic” Alberta AI data centre investment, sources say

Meta Platforms, the parent company of Facebook, Instagram and WhatsApp, is behind a massive artificial intelligence data centre planned for Sturgeon County, Alberta, Juno News has confirmed.

This is according to several well-placed sources with direct knowledge of the investment, one that all sources agree will be “historic” in magnitude.

The project is expected to involve roughly $13 billion in total investment, though the final figure could still change as it is unclear if the final proposal has been approved and signed off by Mark Zuckerberg and Meta’s board.

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Anthropic Removes “Scary” Secret Claude Tracker After Developer Stumbles Across It

Anthropic has removed hidden detection code from its Claude Code tool after a developer reverse-engineered the binary and exposed how the company was subtly monitoring users in China.

The code, which Anthropic described as an experiment launched in March, used a form of prompt steganography to signal information about a user’s environment back to Anthropic’s servers. It was designed to help detect unauthorized resellers and attempts by other organizations to distill Claude’s capabilities into their own models.

How The Detection Worked

The mechanism was first spotted by a Reddit user known as LegitMichel777, who stumbled on it while trying to restore a disabled feature in Claude Code. A separate developer known as Thereallo independently confirmed the finding the same day, June 30, publishing a technical breakdown of exactly how it worked.

The checks only ran in one specific situation: when a user pointed Claude Code at a different server instead of Anthropic’s own – something companies commonly do when they route their traffic through internal systems or third-party gateways. From there, it checked two things:

  • Whether the user’s computer was set to a Chinese time zone (Shanghai or Urumqi).
  • Whether the new server address matched a hidden list of Chinese AI companies (including well-known names like DeepSeek, Zhipu, and Moonshot) or known resale and proxy services.

If either check came back positive, Claude Code would quietly tweak a line of text called the “system prompt” – background instructions the app automatically sends to the AI model with every request, invisible to the person typing. Specifically, it changed how the date was written in that line:

  • If the user was in a Chinese time zone, the date switched from using dashes to slashes (e.g., 2026/06/30 instead of 2026-06-30).
  • The apostrophe in the phrase “Today’s date is…” was swapped for one of three lookalike characters, each one a different signal, depending on which combination of checks the session had triggered.

None of this was visible to users, or likely even to the AI model itself in normal use – the characters look identical on screen. But Anthropic’s servers could read the difference instantly. The lists of flagged domains and keywords were also scrambled inside the app’s code using a basic encryption trick, so they wouldn’t show up if someone just opened the file and searched for them.

Thereallo called the approach “prompt steganography” – hiding a signal inside ordinary-looking text – and noted it let Anthropic sort and flag sessions without needing any separate, visible tracking system.

Anthropic’s Explanation

Last Tuesday, Anthropic engineer Thariq Shihipar, who works on the Claude Code team, confirmed the feature on X:

“This is an experiment we launched in March that was meant to prevent account abuse from unauthorized resellers and protect against distillation. The team has landed stronger mitigations since then and we’ve actually been meaning to take this down for a while. We merged the PR and this should be fully rolled back in tomorrow’s release.”

Anthropic has stated that unauthorized resellers have been selling access to Claude accounts and subscriptions at steep discounts in certain markets. The company has also publicly documented large-scale efforts by Chinese AI labs to distill its models by querying them at high volume through proxies and fraudulent accounts.

Anthropic removed the detection logic shortly after it became public.

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