A shocking new report has revealed that data brokers were selling the phone location data of European Union officials, exposing what experts now call the EU phone data breach. The discovery has raised urgent questions about whether Europe’s privacy protections work at all.
Journalists across Europe obtained a dataset from a commercial broker that included 278 million location points. Inside were traces from hundreds of government phones, including those used by senior officials working at the European Commission and European Parliament.
The EU phone data breach included thousands of markers that showed where top policymakers lived, worked, and traveled. All of it came from ordinary apps that quietly sent users’ coordinates to data brokers, who then sold the information to advertisers, governments, and private buyers.
According to the report by Netzpolitik, over 2,000 data points belonged to 264 officials, and nearly 6,000 markers came from 750 phones used inside the Parliament. That means the movement of key decision-makers could be reconstructed in detail.
The General Data Protection Regulation (GDPR) was meant to make such practices impossible. Yet, as this EU phone data breach proves, the data trade continues to thrive in Europe because enforcement remains weak. Regulators rarely act against data brokers who claim user consent, even when that consent comes from buried app permissions.
Following the revelation, the European Commission issued new internal guidance to protect staff from tracking. But experts say this is only a temporary fix. “Once location data is sold, it cannot be taken back,” said a privacy researcher. “The EU phone data breach shows that even regulators are not safe.”
Last year’s Gravy Analytics incident in the United States revealed similar patterns. That breach exposed the movements of millions of people, proving how location data can easily be used for surveillance, blackmail, or manipulation.
Device makers like Apple and Google have since added features that anonymize tracking IDs, but these safeguards only work going forward. The data already in circulation from the EU phone data breach cannot be erased.
The breach highlights a growing irony. Europe built its reputation on privacy leadership, but the very institutions enforcing those laws are now caught in their own surveillance net.
Read the original coverage at TechCrunch.
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In a small factory outside Shanghai, a new kind of worker is learning how to move. Its name is AgiBot, a humanoid robot that can be trained by people in real time to assemble electronics, test parts, and pass them down a production line.
AgiBot’s idea is simple but radical. Instead of teaching robots through endless simulation, the company pairs each machine with a human trainer who guides it through a task for about ten minutes. Then the robot learns to repeat it alone. This process, known as real-world reinforcement learning, blends human intuition with machine precision.
It is already being tested by Longcheer Technology, a major Chinese manufacturer that builds smartphones, VR headsets, and other electronics. The AgiBot system allows robots to take on repetitive but high-volume tasks, such as moving components from testing machines to assembly lines, while still adapting to shifting workflows.
Unlike traditional industrial robots that perform rigid motions, AgiBot’s machines learn through touch, vision, and trial. They are not coded to complete one routine forever. They evolve through repetition, much like human workers do.
Behind the system is Jianlan Luo, a UC Berkeley researcher turned entrepreneur. Luo helped pioneer human-in-the-loop robotics research in California before bringing the idea home to Shanghai. At AgiBot, his team of engineers and teleoperators trains robots for different factories across China, from electronics to consumer goods.
Training robots this way takes a surprising amount of human effort. In AgiBot’s training center, hundreds of operators guide robot arms through tasks, generating data that improves the company’s learning models. It is part of a growing trend in robotics where human labor fuels machine intelligence.
“Robots are not replacing workers,” said Yuheng Feng, an AgiBot representative. “They are learning from them.”
Each robot session creates more adaptable code, faster learning cycles, and smarter machines that can move to new production lines without weeks of reprogramming. For manufacturers, that flexibility is gold.
China’s government has made robotics a core focus in its latest five-year plan, alongside artificial intelligence and automation. The country already operates more industrial robots than the rest of the world combined, giving startups like AgiBot a vast playground for scaling quickly.
Experts say this fusion of human skill and robotic learning could define the next phase of manufacturing. “AgiBot is using some of the most advanced reinforcement learning seen outside a lab,” said Jeff Schneider, a Carnegie Mellon roboticist. “If it works as described, it could reshape how factories operate.”
Across the Pacific, startups in the United States are racing to catch up. Companies like Physical Intelligence and Skild are developing similar models that teach robots to adapt to new shapes, arms, and environments. But China’s scale and production speed may give AgiBot a lasting advantage.
AgiBot’s long-term goal is to create humanoid robots that can walk, handle tools, and work alongside people safely. For now, its focus remains clear: give robots a human touch and let them learn from the people who know the work best.
The quiet revolution is already underway, and it is not happening in a lab. It is happening on a factory floor where humans and machines are learning to build the future together.
Read the original coverage at WIRED.
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When US President Donald Trump pardoned Changpeng Zhao, better known as CZ, the crypto industry held its breath. Less than two years ago, the Binance founder had pleaded guilty to failing to maintain an effective anti-money-laundering program. Binance was fined $4.3 billion, forced to leave the US, and placed under a compliance monitor.
Now the man once portrayed as crypto’s outlaw has been recast as a martyr. Trump called him a victim of the previous administration’s “war on crypto.” Zhao’s record is clean again, but the industry is anything but calm.
The pardon, announced in late October, may reshape the balance of power across the US crypto market. With Binance barred from operating in the country, legal experts say the decision could set off a wave of lobbying and regulatory uncertainty. The question is whether the world’s largest exchange will try to come back and what that means for the companies that never left.
What makes this pardon explosive is not only Zhao’s return but the network around him. Binance has ties to World Liberty Financial, a crypto firm co-founded by Trump’s sons. Through an investment deal earlier this year, Binance agreed to take a $2 billion stake denominated in USD1, a coin issued by the Trump family’s company. The arrangement could earn millions in token revenue. That connection has left the industry uneasy, with talk of nepotism and self-dealing flooding crypto forums.
Trump, when asked about Zhao, brushed it off. “I do not know who he is,” he said in a 60 Minutes interview, adding only that his sons are “into crypto.”
For supporters, the pardon corrects what they see as political targeting. Teresa Goody Guillén, a partner at Baker and Hostetler, called Zhao’s sentence unprecedented, noting he was a first-time offender who never committed fraud. But even allies admit the move has blurred the line between policy and personal interest.
Some industry voices are already warning of long-term consequences. Azeem Khan, founder of Miden, called the pardon “a spark for scorched earth.” Others, like venture capitalist Nic Carter, said Trump’s actions confirm a pattern. “He does not care about the appearance of impropriety at all,” Carter said. “His sons have been so active in crypto. It makes everything murkier.”
Inside Washington, that murkiness matters. The industry spent hundreds of millions backing pro-crypto candidates in the 2024 elections. Now, with the political tide shifting, many fear a backlash when power changes hands. Stablecoin laws have passed, but broader blockchain regulation may now stall indefinitely.
For US-based exchanges, the threat is also practical. If Binance reenters the market, it could undercut competitors like Coinbase by slashing fees and absorbing losses to gain users. Coinbase has spent the last year diversifying its business, acquiring derivatives platforms and forging deals with PayPal and American Express to build an ecosystem that locks customers in. “Competition is coming,” Khan said. “That is why Coinbase has been so aggressive.”
The irony is that, legally speaking, the pardon changes little. Zhao and Binance are still bound by the plea agreements that ban them from operating in the US. His admissions remain on record. But perception is power and perception in crypto moves markets faster than regulation ever can.
Zhao seems to understand this. In a post on X, he thanked Trump and wrote, “We will do everything we can to help make America the capital of crypto.” Shortly afterward, he quietly changed his bio, removing “ex-binance” from his profile.
Binance still processes over $20 billion in trades each day, nearly eight times more than Coinbase. Its return to the US, even symbolically, could redraw the global crypto map. For now, the blockchain world stands divided: part celebration, part disbelief, and part fear that the same forces that built crypto’s freedom might end up capturing it.
Read the original coverage at WIRED
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Startups are often romanticized as engines of innovation, but according to Chungin Roy Lee, cofounder and CEO of the AI app Cluely, the reality is less glamorous. Most startups do not fail because of weak products. They fail because nobody sees them.
Lee told TechCrunch at Disrupt 2025 that engineers, no matter how brilliant, “just cannot make good content.” The internet rewards bold, authentic, and personal voices, not polished corporate messaging. For a startup, failing to get attention can be fatal, even if product-market fit exists.
Cluely launched earlier this year as an AI tool that helps software engineers cheat on job interviews. While the company has since removed that messaging from its site, the platform still offers real-time guidance by viewing users’ screens and feeding them answers. Lee insists the startup’s focus is on distribution, not gimmicks. The company is betting big that visibility drives growth.
A tongue-in-cheek video posted by Cluely earlier this year went viral, showing Lee trying to impress a date using the app. It was a demonstration of how personality, humor, and virality can outweigh product polish. Lee emphasizes that Cluely is not about rage-bait or trickery. “I do not even think I rage-bait,” he said. “It is probably just my personality. I try to be honest and authentic.”
The San Francisco startup raised $15 million in June, led by Andreessen Horowitz. Lee says the goal is ambitious: Cluely must become “the biggest thing” on Instagram and TikTok. Distribution is central to the company’s DNA. There are only two job titles at Cluely: engineer or influencer. Every team member must excel in their role and have a significant social following.
Traditional marketers are unlikely to succeed in this environment. According to Lee, “You can have a 35-year-old marketer who scrolls as much as they want. For some reason, they just will not have the viral sense to come up with hooks that are capable of generating 10 million views.” Understanding young culture, tapping into trends, and leveraging authenticity are more important than strategy documents.
Cluely’s approach extends to compensation. Engineers are offered up to $1 million in base salary, and designers $250,000 to $350,000, alongside equity. “I only care about how good your work is,” Lee wrote on LinkedIn. “I do not care about school, experience, age, citizenship status, etc. Please be world-class.”
For founders and early-stage startups, the lesson is clear: engineering brilliance is not enough. Success is defined by visibility, cultural relevance, and the ability to engage an audience at scale. Distribution, not just innovation, separates startups that flop from those that thrive.
Read the original coverage at Business Insider.
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The International Criminal Court is officially breaking away from Microsoft Office. In a move that signals a deeper shift in European digital sovereignty, the court confirmed it will migrate to Open Desk, a German-built open source platform designed for public institutions.
At first glance, this might sound like a simple software swap. But in the world of global politics and cybersecurity, it feels closer to a geopolitical statement. The ICC’s decision underscores Europe’s growing discomfort with depending on American tech giants for critical government operations.
The change comes after years of tension between the court and the United States. During Donald Trump’s presidency, Washington imposed sanctions on the ICC’s chief prosecutor, Karim Khan. At one point, Microsoft even deactivated Khan’s email account, though the company later denied it. The episode highlighted just how fragile the digital ties between international bodies and US-based cloud providers can be.
A Microsoft spokesperson told Euractiv that the company “values its relationship with the ICC” and believes nothing will prevent it from continuing to serve the court. But the tone of Europe’s digital agenda has shifted. Sovereignty is the new keyword in Brussels.
Open Desk was developed by the German Centre for Digital Sovereignty of the Public Administration, better known as Zendis. It is part of a broader European effort to build open, secure, and independently maintained software for public institutions. Four EU countries recently joined forces to establish a shared framework for digital sovereignty, a foundation that Open Desk directly supports.
The ICC’s move could spark a domino effect. Other international organizations and EU agencies are already evaluating alternatives to US software providers. The reasoning is simple: political stability should not depend on a company’s terms of service or a country’s foreign policy.
The shift also fits into a wider European narrative. From cloud computing to defense AI, the idea of strategic autonomy has become central to EU tech policy. Projects like Gaia-X and now Open Desk reflect a growing realization that Europe cannot lead in regulation alone, it must also lead in infrastructure.
Still, practical questions remain. Can an open source suite match Microsoft’s scale, usability, and integrations? For global institutions like the ICC, collaboration happens across borders and jurisdictions, often under strict confidentiality. Rebuilding those workflows within an open source environment will require both trust and investment.
Supporters of the move see this as the beginning of a longer, necessary transition. As one digital sovereignty advocate in Berlin put it, “We have regulated Big Tech for years. Now we are finally learning how to replace it.”
The ICC’s decision is more than a procurement choice. It is a signal that Europe’s era of digital dependence is starting to end. The question is whether its open source future will be as seamless as its ambitions suggest.
Read the original coverage at Euractiv.
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AI browsers cybersecurity experts are sounding the alarm. The tools meant to make the internet smarter may be creating one of the most fragile digital frontiers yet.
OpenAI and Microsoft have both introduced AI browsers that can think, read, and act. ChatGPT Atlas and Copilot Mode are part of a race to blend search, memory, and automation inside the browser itself. The pitch sounds convenient. But cybersecurity researchers warn it might also be catastrophic.
A new Verge report by Robert Hart reveals just how deep the risks go. Vulnerabilities in OpenAI’s Atlas and Perplexity’s Comet already allow attackers to inject hidden instructions into a browser’s memory. Once triggered, those commands can steal data, execute malicious code, or quietly share information you never meant to give away. The term prompt injection has already become a staple in cybersecurity discussions, and the AI browsers cybersecurity landscape is changing faster than security standards can keep up.
Professor Hamed Haddadi of Imperial College London described the problem simply: “The attack surface has never been wider.” Each time the browser learns, it also remembers, storing more of what users read, type, and click. This creates enormous potential for tracking and profiling. The AI browsers cybersecurity problem is not just about bad actors. It is about the system itself becoming too curious.
UC Davis researcher Yash Vekaria says these browsers know more about you than traditional ones ever could. Every click and conversation feeds a growing behavioral map that can be exploited by advertisers and hackers alike. With stored payment data, logins, and search histories, a single compromised session could reveal more than a user realizes.
The market rush is another key factor. Lukasz Olejnik, a cybersecurity researcher at King’s College London, compares this moment to the early days of mobile apps, when convenience outpaced security. “Expect risky vulnerabilities to emerge,” he said. The AI browsers cybersecurity problem is not theoretical. It is historical. We have seen this cycle before with extensions, macros, and permissions. The tools evolve faster than our ability to defend against them.
The threat grows sharper when browsers begin acting on their own. Agentic features let the browser make decisions, click links, and submit forms automatically. That means attackers can trick it into sharing data or performing actions without the user’s knowledge. Prompt injections can even hide inside images or code snippets, invisible to the naked eye.
The only reliable defense, experts say, is to slow down. Professor Shujun Li of the University of Kent advises users to disable automated features unless absolutely necessary. “Browsers should start in an AI-free mode,” he says. The best cybersecurity sometimes begins with saying no.
Convenience is always the lure. But each shortcut we take online erodes one more layer of human awareness. The AI browsers cybersecurity problem is not just about code. It is about trust. We have built machines that are learning how we think. Now we need to make sure we still think for ourselves.
Read the original report by Robert Hart at The Verge.
For more Laterstack analysis, explore the Information Sharing Act and AI’s energy gap issues.
Every so often, something happens in tech that feels small at first but turns out to change everything later. NVIDIA’s new NVQLink might be one of those moments.
The company announced it’s Nvidia nvqlink quantum computing at its Global Technology Conference in Washington. NVQLink is an open system that lets quantum processors connect directly to GPU-based supercomputers. In simple terms, it lets the two types of machines finally work together as one.
Speaking of GPUs… Have you read about the biggest EU probe in history over GPUs? Read more HERE
Jensen Huang, NVIDIA’s CEO, said it could become the foundation for hybrid computing. He described NVQLink as the Rosetta Stone of the quantum era. For once, that kind of metaphor fits. The system lets quantum and classical machines speak the same language, and that opens up a completely new world of computing.
Here is why this matters. Quantum computers are powerful, but they are unstable. Their qubits are sensitive to even the smallest noise or temperature change. They need constant calibration, error correction, and coordination with classical processors. Until now, that back-and-forth took too long. NVQLink removes that lag by giving both systems a direct and fast connection, so corrections and commands can happen instantly.
This was not built in isolation. NVIDIA worked with nine national labs, seventeen quantum hardware companies, and five controller builders to design it. The list includes Brookhaven, Los Alamos, and Lawrence Berkeley, along with companies like IonQ, Rigetti, and Pasqal. It is one of the most diverse collaborations the quantum field has seen so far.
The new system also fits into NVIDIA’s existing CUDA-Q platform, which lets researchers use CPUs, GPUs, and quantum processors together in one environment. That means the barrier between simulation, data analysis, and quantum execution is starting to fade. For scientists, that is a huge step forward.
The U.S. Department of Energy sees it as more than just an engineering milestone. Energy Secretary Chris Wright said it is part of a national effort to maintain leadership in high-performance computing. His point is simple: whoever builds the most efficient bridge between quantum and classical computing will probably lead the next wave of scientific progress.
Of course, this does not mean we suddenly have a commercial quantum computer in every lab. The physics are still hard. Qubits still lose coherence. Cooling systems still cost millions. But this changes where the real bottleneck is. The connection between quantum and classical systems has always been the weak link. NVQLink turns that weak link into a highway.
If you zoom out, this feels like more than an infrastructure story. It feels like the start of a new mindset in computing. The race is not about replacing classical computers with quantum ones. It is about making them work together, each doing what it does best.
That has always been the story of progress in computing. First, we connected terminals to mainframes. Then we connected personal computers to networks. Then we connected networks to the cloud. Now, we are connecting the cloud to quantum systems. Each step has made the world a little more integrated, a little more powerful, and a little harder to define.
NVQLink might not grab headlines outside the tech world right now, but inside research circles, this is a clear turning point. For the first time, the bridge between classical and quantum computing is not a theory. It is real, and it has a name.
This coincides with Nvidia’s leading effort to gather everyone to join in on their cause for data growth, from athletes to movie stars. Check out more HERE .
Read Matt Swayne’s original article on nvidia nvqlink quantum computing here: NVIDIA Launches NVQLink to Bridge Quantum and Classical Supercomputing
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Most people who talk about blockchain never look at one. They repeat the same line: each block contains the cryptographic hash of the previous block. It sounds right, but it is not quite true.
John D. Cook decided to look closer. He downloaded two consecutive Bitcoin blocks and inspected their raw bits. His post shows how the blocks actually connect, not in theory, but in hexadecimal reality.
He finds that what links one block to the next is not the hash of the whole block, but the hash of its header. The difference matters. The header is a compact summary of the block’s structure, holding the Merkle tree root that represents all transactions beneath it. Change a single transaction, and that root changes too, which changes the header and the hash. The entire chain reacts.
Cook takes readers line by line through what that header looks like. Magic numbers, byte order, proof of work, details that rarely enter the conversation outside engineering circles. He even shows the command line instructions that compute the double SHA256 hash, the exact sequence that ties Bitcoin together.
Along the way, he reveals how even trusted explanations are often half-truths. The zeros at the end of a hash, for example, are not decorative. They show the computational labor that earned the block its place in the chain.
Reading his breakdown, you remember that blockchains are not metaphors about trust or revolution. They are data structures built by people who value exactness. Beneath every slogan, there are bytes, hashes, and the quiet persistence of those who check the math for themselves.
It is refreshing to see a post like Cook’s at a time when technical precision often gets traded for storytelling. He reminds us that real understanding begins where the abstractions stop, at the level of the bits themselves.
Read John D. Cook’s original piece here: How blocks are chained in a blockchain
The Deckmate 2 is supposed to make poker fair. It shuffles a deck in seconds with computer precision and a built-in camera to verify that every card is accounted for. But that same precision made it a perfect tool for cheating.
This week, the United States Justice Department unsealed an indictment against 31 people accused of running a vast underground poker network that used hacked shufflers to steal millions. Among those charged are alleged members of organized crime families and two well-known NBA names, Portland Trail Blazers coach Chauncey Billups and former player Damon Jones.
According to prosecutors, the group ran high-stakes poker games across New York, the Hamptons, and Miami. Players were enticed by the chance to gamble with celebrities, unaware that the games were rigged from the start. Modified Deckmate 2 machines transmitted the order of the cards via Bluetooth to accomplices who used subtle hand signals to guide the betting.
Over several years, the operation allegedly took in more than seven million dollars. The FBI described the scheme as a fusion of technology and deception that funneled money into the Cosa Nostra crime network.
The Deckmate 2 has been under scrutiny since researchers at IOActive exposed vulnerabilities in 2023. They demonstrated how a small device could be plugged into the shuffler’s USB port to rewrite its code and access its internal camera. From there, a cheater could know every card in the deck before it was dealt.
Wired later tested the exploit in a live game, showing that a partner with a connected phone app could predict every hand on the table. It was a proof of concept that mirrored the same technique now appearing in the indictment.
The alleged poker ring went further. Prosecutors claim they used pre-rigged machines that transmitted deck data directly to an operator outside the room. That person then sent the information to a player acting as a “quarterback,” who silently directed the team of cheaters during the game.
Some shufflers were even stolen at gunpoint to ensure control over their internal systems.
Light and Wonder, the company that makes the Deckmate 2, said it has since patched the vulnerabilities by disabling the USB port and tightening code verification. But experts warn that many secondhand and unregulated machines remain vulnerable.
Doug Polk, a professional poker player and card house owner, put it simply in an earlier interview: if there is a camera that can see the cards, someone will eventually find a way to read it.
The indictment also details other cheating methods that sound like scenes from a heist film: infrared-marked cards, chip trays with hidden scanners, and special contact lenses that reveal invisible markings.
These tools have long circulated in underground gambling networks, but combining them with modern hacking blurred the line between old-school scams and modern cybercrime.
For the victims, the mix of glamour and technology was irresistible. Private games with famous athletes promised exclusivity and excitement. Instead, players walked away cleaned out by a digital con that looked like luck.
In Baltimore County, a student was handcuffed after a school security system flagged what it believed to be a firearm. The object was a bag of Doritos.
Seventeen-year-old Taki Allen was sitting outside Kenwood High School on Monday when officers approached with guns drawn. “I didn’t know what was happening until they told me to get on the ground,” he told local station WBAL-TV. “I was just holding a Doritos bag.”
The system that triggered the alert uses artificial image recognition to identify potential weapons through school security cameras. When it detects what it interprets as a threat, it sends an automatic notification to administrators and law enforcement.
The error caused confusion and fear among students who witnessed the incident. School officials later issued a statement acknowledging how distressing the event had been and offered counseling support.
Baltimore County Police confirmed they responded to a report of a suspicious person but found no weapon. “It was determined the subject was not in possession of any weapons,” a spokesperson said.
The incident underscores growing questions about algorithmic oversight in environments where mistakes carry immediate human consequences. Schools and municipalities have rushed to adopt automated detection tools designed to spot firearms, fights, or intrusions in real time. But these systems often rely on training data that struggles to interpret complex or ambiguous movements, lighting, or everyday objects.
False positives can turn ordinary moments into police encounters. Civil rights groups and technologists have warned that these tools expand surveillance without sufficient transparency or accuracy benchmarks.
Kenwood High’s case is not the first misfire for automated security in public spaces. As image-based recognition spreads into schools, malls, and airports, the tradeoff between safety and privacy continues to narrow.
For Allen and his classmates, that tradeoff became personal. A snack mistaken for a threat led to guns drawn, a search, and a lesson that even the safest spaces are not immune to machine error.