A critique published in Nature Wednesday calls the basic technology behind Microsoft’s “breakthrough” quantum computing chip the Majorana 1 into question. Microsoft unveiled the chip in February 2025 and said it featured a brand-new technology known as a topological qubit. Topological qubits, they said, would be the “building blocks” for their future quantum computer. Microsoft announced the next generation chip Majorana 2 at Build earlier this month.
Technology
How scammers build a profile on you using data brokers
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Go to any people finder site right now and type in your name. What comes back might shock you: your age, home address, phone number, the names of your relatives, where you used to live and even what your property is worth.
You didn’t put that there, and you never consented to it. Still, it’s out there, and anyone with an internet connection can see it.
Scammers figured this out a long time ago. Since then, they’ve turned it into a system for targeting you, your parents and your kids.
So how does it actually work, and more importantly, what can you do to stop it?
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HOW TO REMOVE YOUR PERSONAL INFO FROM PEOPLE SEARCH SITES
A single person search result can reveal your address, relatives and years of personal history in seconds. (Kury “CyberGuy” Knutsson)
How scammers find your personal data online
Before a criminal sends a phishing email or makes a call, they do their homework. Importantly, they don’t need to hack anything. Instead, they use the same public websites that anyone can access.
In less than 10 minutes, a scammer can build a detailed profile on you using data broker sites like Spokeo, Whitepages, BeenVerified and Intelius. Here’s what that profile looks like and how they build it step by step.
Step 1: How scammers search your name on people finder sites
It starts simply. A scammer types your name into a search site. Within seconds, they see results like:
John M. Patterson | Age: 61 | Cleveland, OH
- Also known as: John Michael Patterson
- Current address: [your street address]
- Previous addresses: 4 records found
- Phone numbers: 2 found
- Email addresses: 3 found
- Relatives: 5 found
That is the starting point. Many sites show partial data for free. That is often enough to confirm identity. Full reports cost only a few dollars, so access is easy. Scammers can repeat this process hundreds of times a day, building detailed profiles with very little effort.
Step 2: How scammers map your family and relatives
Next, this is where things get personal. Data broker profiles show more than your name. They reveal your family network.
That often includes:
- Spouse or partner
- Children
- Parents
- Siblings
- Roommates
As a result, scammers can target more than one person. For example, they may learn that your elderly parent lives alone or your child just moved. Because of that, scams like the grandparent scam feel real instead of random.
Step 3: How scammers use your address history
At this point, your address history becomes critical. It is not just about where you live. Instead, scammers use it to:
- Verify identity
- Find relatives
- Build trust
For example, referencing a past address makes a caller sound legitimate. That detail alone can lower suspicion.
Step 4: How scammers use your financial data
More importantly, data brokers also reveal financial clues. These may include:
- Estimated income
- Home value
- Ownership status
- Length of residence
This information comes from public records, not hacking. Because of this, scammers tailor their approach. Higher-income targets may see investment scams.
Others may get job or rental scams instead.
GOOGLE SEARCH LED TO A COSTLY SCAM CALL
Scammers use data broker profiles to map your family and build more convincing, targeted attacks. (Kurt “CyberGuy” Knutsson)
Step 5: How scammers verify and cross-check your data
Before launching a scam, criminals often double-check everything. They don’t rely on just one site. Instead, they compare multiple data broker profiles, social media accounts and public records to confirm details are accurate.
For example, they may:
- Match your address across different sites
- Check Facebook or LinkedIn to confirm family relationships
- Look for recent moves, job changes or life events
Because of this, the profile becomes more reliable. That extra step is what turns a guess into something that feels real.
Step 6: How scammers create targeted scams
At that point, they have everything they need. They know your name, family, address and financial details. Now the scam becomes highly specific.
By the time you hear from them, they already know enough to sound like someone you trust.
- They may call your parent pretending to be you
- They may bypass bank security questions
- They may send texts that look like your child
- They may send emails that reference your life
As a result, the scam feels believable.
Data broker scams are already being prosecuted
This has already landed in court. The U.S. Department of Justice has prosecuted companies like Epsilon, Macromark Inc. and KBM Group for selling data to scammers. Epsilon alone paid $150 million to victims.
At the same time, data tied to the FBI Internet Crime Complaint Center shows more than half of fraud cases involving older Americans were linked to exposed personal data. That shows how serious this problem has become.
Why is your personal data on data broker sites
You do not need to sign up for these sites. Instead, your data comes from many sources, including:
- Voter records
- Property records
- Court filings
- Social media
- Marketing surveys
- Loyalty programs
- Phone directories
- Other data brokers
Because of this, your information spreads quickly.
Why your data keeps reappearing online
Even after removal, your data often comes back. Data brokers constantly update their databases. They buy and resell fresh records. Because of that, one-time removal is not enough.
By the time a scam reaches you or your family, it is often built on real data pulled from multiple public sources. (Wei Leng Tay/Bloomberg)
How to disrupt a scammer’s research before they reach your family
The goal isn’t to disappear completely. It’s to make the profile messy enough, incomplete enough and hard enough to find that scammers move on to easier targets.
Here’s what you can do:
- Search for yourself first. Go to Spokeo, Whitepages, BeenVerified or any other people search site, and look up your own name. See exactly what’s there before a scammer does. That snapshot is your starting point.
- Submit opt-out requests manually. Every major data broker is required to honor removal requests. The catch: There are hundreds of them, each with its own process, and they relist your information regularly. It’s a full-time job.
- Use an automated removal service. This is where I strongly recommend a data removal service. Instead of spending hours submitting individual opt-out forms, a data removal service sends removal requests to 420-plus data brokers on your behalf and keeps sending them when your data reappears. Because it will reappear.
- Set up family alerts. Tell your elderly relatives that you will never ask for money via text from an unknown number. Establish a code word. Scams work because they create panic. A simple family protocol breaks the spell.
- Change your security questions. If your bank still uses “mother’s maiden name” or “city you were born in” as verification, that information is likely already on a data broker site. Switch to nonsense answers that only you know and store them in a password manager.
Check out my top picks for data removal services and get a free scan to find out if your personal information is already out on the web by visiting Cyberguy.com
Get a free scan to find out if your personal information is already out on the web: Cyberguy.com
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Kurt’s key takeaways
This kind of scam works because it feels personal. When someone knows your name, your family and even where you used to live, your guard drops. That is exactly what criminals are counting on.
The uncomfortable truth is that your information is already out there, often in more places than you realize. You do not need to panic, but you do need to be proactive. The more you limit what is easily accessible, the harder it becomes for someone to build a convincing story around you. Start with a simple search of your own name. That one step can completely change how you think about your digital footprint. From there, take action to remove what you can and protect what you cannot.
If a stranger can build a detailed profile on your family in minutes, what does that say about how much of your life is already exposed online? Let us know by writing to us at Cyberguy.com
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Robots have gotten very good at moving fast, repeating steps and doing jobs that would wear you and me out. But ask a robot to pick up something delicate, oddly shaped or slightly different from the last item it handled, and things can get a little complicated quickly.
That is where a new collaboration between ABB Robotics and PSYONIC comes in. ABB Robotics is working with PSYONIC, a California bionics company, to explore whether real-world touch and motion data from human prosthetic use can help train robotic arms.
In other words, the same kind of bionic hand that helps a person grip a tool, pick up a fragile object or adjust pressure in real time could help teach robots how to do those tasks better.
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SOFT ROBOTIC ARMBAND GIVES PROSTHETIC HAND USERS NATURAL CONTROL
The PSYONIC Ability Hand can capture touch, motion and grip-force data from real human prosthetic use. (ABB Robotics)
How a bionic hand could teach a robot
The collaboration centers on PSYONIC’s Ability Hand and ABB’s GoFa cobot. The Ability Hand was originally developed for prosthetic use. It has multi-articulating fingers, pressure sensors, vibration feedback and flexible mechanics that help it conform to irregular objects. That combination is important because human grip isn’tt one fixed action. You hold a coffee cup differently than a screwdriver. You handle an egg differently than a phone. Most of us do that without thinking about it.
For robots, that instinctive adjustment is hard. ABB and PSYONIC want to explore how movement, contact and grip-force data from the Ability Hand can help train robots to handle objects that are fragile, uneven or unpredictable. ABB’s GoFa cobot brings the industrial side of the equation, offering the accuracy and repeatability needed to test those movements in a controlled way. The result could be a robot arm that learns from real human handling data, then applies that information to factory and warehouse tasks.
Why robot grip is such a hard problem
Industrial robots can already lift, move, weld, sort and assemble with impressive speed. However, many still struggle when a task involves subtle touch. Think about a robot picking up a soft package, a medical component or a part that shifts slightly on a conveyor belt. Too much pressure can damage the item. Too little pressure can make the robot drop it. A tiny change in angle can throw off the whole process.
JOB-KILLING ROBOT LEARNS AT WORK, AND IT’S COMING TO THE FACTORY FLOOR
That is why gripping and dexterity remain major challenges in automation. ABB calls this a key part of Autonomous Versatile Robotics, or AVR, its vision for robots that can sense, reason, move and handle objects with precision in changing environments.
Marc Segura, president of ABB Robotics, put it this way: Human dexterity remains “one of the most difficult things to replicate in industrial-grade robotics.” He said the collaboration with PSYONIC could help “close the long-standing gap” between human and robot dexterity. That gap is where this technology could make a real difference.
What makes the PSYONIC Ability Hand different
The PSYONIC Ability Hand was built to help people. It uses myoelectric control, touch sensing and compliant mechanics in a lightweight design. Its sensors can detect pressure during a grip, while vibration feedback can help communicate touch back to the person using it. That same sensing ability could be valuable for robots.
AI ENABLES PARALYZED MAN TO CONTROL ROBOTIC ARM WITH BRAIN SIGNALS
PSYONIC says the Ability Hand can capture detailed data about movement, contact and grip force. When that hand is used by people in real-world situations, it can generate a more natural dataset than a lab-only robot demonstration.
ABB’s GoFa cobot is being used to test how bionic hand data could help robots handle delicate and irregular objects. (ABB Robotics)
Dr. Aadeel Akhtar, founder and CEO of PSYONIC, called dexterous manipulation “a data challenge as much as a hardware challenge.” That line really gets to the heart of this. Better robot hands are important. Yet the training data behind those hands may be what decides how useful they become in real workplaces.
Where bionic hand data could show up first
ABB and PSYONIC say this work could apply across automotive, aerospace, packaging, logistics and life sciences. That makes sense. These are industries where robots already play a major role, but where delicate or variable handling can still slow things down. A robot that can better adjust its grip could help with fragile components, oddly shaped products, soft packaging or repetitive tasks that are tough on the body.
HUMANOID ROBOTS HANDLE QUALITY CHECKS AND ASSEMBLY AT AUTO PLANT
The International Federation of Robotics has also pointed to advanced gripping and digital integration as a way to reduce engineering time by up to 30%. That’s important for companies because automation often gets delayed by setup, tuning and custom engineering. If touch-enabled robotic hands can reduce some of that work, companies could deploy robots faster and use them in more flexible ways.
How touch-trained robots could change factory work
There is a hopeful side to this. Robots that handle repetitive or ergonomically challenging work could reduce strain on people. That could mean fewer workers stuck doing the same painful motion all day. However, there is also a bigger labor question here. More capable robots could take on tasks that once seemed too variable to automate. That may affect how companies hire, train and assign work in the future.
The most useful version of this technology would support people instead of simply replacing them. For example, robots could handle the repetitive gripping while workers focus on oversight, quality checks, machine setup and higher-skill work.
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Kurt’s key takeaways
ABB Robotics and PSYONIC are taking a different approach to one of robotics’ hardest problems: touch. Instead of training robots only in a lab, they want to use real movement and grip data from a bionic hand that people already use. That could help robots become better at delicate, variable tasks that have traditionally been hard to automate. It could also push industrial robots closer to working safely and effectively around humans in more settings. But the human side should not get lost in the excitement. If robots are going to learn from human touch, companies need to be clear about data use, workplace impact and safety testing.
The collaboration could help robots become more useful in factories, warehouses and other workplaces where precise grip matters. (ABB Robotics)
Would you feel comfortable knowing a robot at work was trained using real human touch data? Let us know by writing to us at CyberGuy.com.
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- Plus, you’ll get instant access to my Ultimate Scam Survival Guide free when you join.
Copyright 2026 CyberGuy.com. All rights reserved.
Amazon’s Prime Day is now in its second day, and whether you’re looking for a new pair of wireless earbuds or a smartwatch, there’s a good chance you’ll find a discount. The Apple Watch Series 11 has already dropped to a new low price, while the AirPods Pro 3 are discounted to $179. With Tim Cook warning that price hikes are coming, now may be the moment if you’ve been eyeing one of the company’s devices.
Below are the best Apple deals currently available. Some are exclusive to Prime Day, while others are simply great discounts we think are worth highlighting. We’ll continue updating this guide throughout Prime Day, highlighting more deals as they become available.
Earbud and headphone deals
Update, June 24th: Adjusted prices and availability, and added deals for Apple’s MagSafe Charger as well as the Apple Magic Keyboard.
But in a peer-reviewed article, Henry Legg, a physicist at the University of St Andrews, reanalyzed Microsoft’s data on their device and argued that the company’s researchers did not conclusively demonstrate a working topological qubit in the first place.
Theory predicts that the electrons in this wire behave in a collective pattern known as a Majorana particle, for which the chip is named.
Proponents of quantum computing predict that the technology’s computational abilities will advance new medicine discovery, encryption, and machine learning. Companies like Google and IBM have already demonstrated more advanced machines than Majorana 1 or 2, although presently, no one has conclusively gotten any quantum computer to perform anything useful. But Microsoft claimed that Majorana 1, and subsequently Majorana 2, paved their path toward a practical quantum computer.
Microsoft’s design, unique among quantum computing companies, involves a tiny wire, thinner than a human hair, made of the semiconductor indium arsenide stuck to a superconductor. Theory predicts that the electrons in this wire behave in a collective pattern known as a Majorana particle, for which the chip is named. Microsoft wants to encode information in the properties of the Majorana particle. (A topological qubit is to a Majorana particle as a transistor is to silicon.)
Proponents of the Majorana particle think it is promising qubit material because theory predicts that when formed into topological qubits, the Majorana should compute with fewer errors than competing materials, such as superconducting circuits pursued by IBM. This suggests that ultimately, fewer topological qubits are needed to scale up to a useful quantum computer.
That is, if Microsoft has actually made a Majorana particle. “They haven’t convincingly shown that they have Majoranas,” Legg told The Verge. “You can’t make a qubit if you don’t have the Majoranas.”
In Legg’s critique, he writes that what Microsoft claims as a signature of the Majorana particle could actually be from the formation of quantum dots, which are electron-containing structures, in the device. Quantum dots would not be useful for building the quantum computer. He also writes that Microsoft cherry-picked their data.
“You can’t make a qubit if you don’t have the Majoranas.”
Microsoft’s team published a rebuttal in Nature disputing Legg’s interpretation of their data. Legg’s critique “does not constitute a substantial scientific challenge to our findings,” the Microsoft team wrote. Legg has not “proposed an alternative model that fits all of our data,” Chetan Nayak, a physicist leading Microsoft’s quantum team, told The Verge.
Legg first posted his critique on the online physics repository arXiv on February 26, 2025, within a week of Microsoft’s Majorana 1 announcement. It took a year for Nature to conduct a peer review and publish his article.
Meanwhile, on June 2, Microsoft announced a new chip, the Majorana 2, featuring what they claimed was the next generation of their topological qubits. The company says they can build a “scalable quantum computer” by 2029. “We 100% stand behind our results,” Nayak told The Verge. “We stand by our roadmap. We stand behind our long-standing commitment to scientific rigor and dialogue.”
Legg says the company’s characterization of Majorana 2, which Microsoft wrote in a non-peer reviewed manuscript, suffers from similar problems he pointed out a year ago. “Nothing in this [manuscript] resolves the fundamental issues that so many scientists have with this company’s previous claims,” Legg told The Verge.
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