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Scientists create AI neural net that can unlock digital fingerprint-secured devices
Computer scientists at New York University and Michigan State University have trained an artificial neural network to create fake digital fingerprints that can bypass locks on cell phones. The fakes are called “DeepMasterPrints”, and they present a significant security flaw for any device relying on this type of biometric data authentication. After exploiting the weaknesses inherent in the ergonomic needs of cellular devices, DeepMasterPrints were able to imitate over 70% of the fingerprints in a testing database.
An artificial neural network is a type of artificial intelligence comprising computer algorithms modeled after the human brain’s ability to recognize patterns. The DeepMasterPrints system was trained to analyze sets of fingerprint images and generate a new image based on the features that occurred most frequently. This “skeleton key” could then be used to exploit the way cell phones authenticate user fingerprints.
In cell phones, the necessarily small size of fingerprint readers creates a weakness in the way they verify a print. In general, phone sensors only capture a partial image of a print when a user is attempting to unlock the device, and that piece is then compared to the phone’s authorized print image database. Since a partial print means there are fewer characteristics to distinguish it than a full print, a DeepMasterPrint needs to match fewer features to imitate a fingerprint. It’s worth noting that the concept of exploiting this flaw is not unique to this particular study; however, generating unique images rather than using actual or synthesized images is a new development.
The team involved in the study resulting in the DeepMasterPrint creation initiated it as part of the ongoing assessment of vulnerabilities in fingerprint recognition systems. Finding exploitable flaws and fixing them is a constant battle in all digital systems with a security component. With this reality in mind, the scientists determined that merely exposing the flaws of fingerprint systems would not provide an effective solution; a working example of how attacks could be executed provides more specific data for researchers to design around and protect against. Creating the DeepMasterPrint system was meant to address this need.
The results revealed by the DeepMasterPrint system are concerning for anyone relying on fingerprint authentication on their smartphones. Scientists compared the generated fake prints against templates generated by VeriFinger 9.0 SDK, Bozorth3, and Innovatrics IDKit 5.3 SKD, all of which are software systems used in fingerprint authentication systems worldwide. At a low false match rate, i.e., strict match requirements for authentication, the fake print generated by DeepMasterPrint could imitate 23% of the fingerprints in the test database. At a slightly higher false match rate that was still within standard phone authentication limits, the fake print imitated 77% of the test fingerprints.
The scientists in this study did not create physical fingerprints to try and unlock actual phones, leaving that work to be done in the near future. However, even though the successful DeepMasterPrints have yet to be tested in true applications rather than a virtual environment, the data gathered confirmed the initial security concerns which inspired the experiment. Fingerprints are being used as identity verification in a growing number of applications beyond cell phone security, i.e., unlocking entryways, payment authentication, etc. The DeepMasterPrint system is another tool to help researchers guard their security as biometric authentication continues to expand.
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Tesla pulls back the curtain on Cybercab mass production
Tesla’s Cybercab drives itself off the Gigafactory Texas line in a striking new production video.
Tesla has provided a first look from inside a production Cybercab as it drove itself off the assembly line at Gigafactory Texas. The video footage, posted on X, opens on the factory floor with robotic arms and assembly equipment visible through the Cybercab windshield, and follows the car through a branded tunnel marked “Cybercab”, before autonomously navigating itself to a holding lot.
The first Cybercab rolled off the Giga Texas production line on February 17, 2026, with Musk writing on X, “Congratulations to the Tesla team on making the first production Cybercab.” April marked the official shift to volume production. The Giga Texas line is being prepared to produce hundreds of units per week, with 60 units already spotted on the Gigafactory campus earlier this month.
Purpose-built for autonomy
Cybercab in production now at Giga Texas pic.twitter.com/Y9qG3KyWBa
— Tesla (@Tesla) April 23, 2026
The Cybercab was first revealed publicly at Tesla’s “We, Robot” event in October 2024 at Warner Bros. Studios in Burbank, California, where 20 pre-production units gave attendees rides around the studio lot. Musk said he believed the average operating cost would be around $0.20 per mile, and that buyers would be able to purchase one for under $30,000. The two-seat design is deliberate. Musk noted that 90 percent of miles driven involve one or two people, making a compact two-passenger vehicle the most efficient configuration for a fleet-scale robotaxi. Eliminating rear seats also removes complexity and cost, supporting that sub-$30,000 target.
Tesla’s annual production goal is 2 million Cybercabs per year once several factories reach full design capacity. The Cybercab has no steering wheel, no pedals, and relies entirely on Tesla’s vision-based FSD system. What the video shows is the first evidence of that system working not as a demo, but as a production reality, driving itself off the line and into the world.
🚗 Our first ride in Tesla Cybercab last October: pic.twitter.com/kGqIqgJPRn https://t.co/BITCXFhbVd
— TESLARATI (@Teslarati) April 22, 2025
Elon Musk
Elon Musk talks Tesla Roadster’s future
Elon Musk confirmed the Roadster as Tesla’s last manually driven car, with a debut coming soon.
During Tesla’s Q1 2026 earnings call on April 22, Elon Musk made a brief but notable comment about the long-awaited next generation Roadster while describing Tesla’s future vehicle lineup. “Long term, the only manually driven car will be the new Tesla Roadster,” he said. “Speaking of which, we may be able to debut that in a month or so. It requires a lot of testing and validation before we can actually have a demo and not have something go wrong with the demo.”
That single statement is the entire Roadster update from yesterday’s call, and while it represents another timeline shift, it comes as no surprise with Tesla heads-down-at-work on the mass rollout of its Robotaxi service across US cities, and the industrial scale production of the humanoid Optimus.
The fact that Musk specifically framed the Roadster as the last manually driven Tesla is significant on its own. As the rest of the lineup moves toward full autonomy, the Roadster becomes something rare in the Tesla-sphere by keeping the driver in control. Driving enthusiasts who buy a $200,000 supercar are not doing so to be passengers. They want the physical connection to the road, the feel of acceleration under their own input, and the experience of controlling something with that level of performance. FSD, however capable it becomes, removes that entirely. The Roadster signals that Tesla understands this distinction and is building a car specifically for the people who consider driving itself the point.
Tesla isn’t joking about building Optimus at an industrial scale: Here we go
The specs for the Roadster Musk has teased over the years are genuinely unlike anything in production. The base model targets 0 to 60 mph in 1.9 seconds, a top speed above 250 mph, and up to 620 miles of range from a 200 kWh battery. The optional SpaceX package takes it further, rumored to add roughly ten cold gas thrusters operating at 10,000 psi, borrowed directly from Falcon 9 rocket technology. With thrusters, Musk has claimed 0 to 60 mph in as little as 1.1 seconds. In a 2021 Joe Rogan interview he went further, stating “I want it to hover. We got to figure out how to make it hover without killing people.” Tesla filed a patent for ground effect technology in August 2025, suggesting the hover concept has not been abandoned. The starting price remains $200,000, with the Founders Series requiring a $250,000 full deposit. Some reservation holders placed those deposits in 2017 and are approaching a full decade of waiting.
With production now targeted for 2027 or 2028 at the earliest, the Roadster remains Tesla’s most audacious promise and its longest-running delay. But if what Musk is testing lives up to even half of what he has described, the demo alone should be worth waiting for.
Elon Musk says the Tesla Roadster unveiling could be done “maybe in a month or so.”
He said it should be an extraordinary unveiling event. pic.twitter.com/6V9P7zmvEm
— TESLARATI (@Teslarati) April 22, 2026
Elon Musk
Tesla confirmed HW3 can’t do Unsupervised FSD but there’s more to the story
Tesla confirmed HW3 vehicles cannot run unsupervised FSD, replacing its free upgrade promise with a discounted trade-in.
Tesla has officially confirmed that early vehicles with its Autopilot Hardware 3 (HW3) will not be capable of unsupervised Full Self-Driving, while extending a path forward for legacy owners through a discounted trade-in program. The announcement came by way of Elon Musk in today’s Tesla Q1 2026 earnings call.
🚨 Our LIVE updates on the Tesla Earnings Call will take place here in a thread 🧵
Follow along below: pic.twitter.com/hzJeBitzJU
— TESLARATI (@Teslarati) April 22, 2026
The history here matters. HW3 launched in April 2019, and Tesla sold Full Self-Driving packages to owners on the understanding that the hardware was sufficient for full autonomy. Some owners paid between $8,000 and $15,000 for FSD during that period. For years, as FSD’s AI models grew more demanding, HW3 vehicles fell progressively further behind, eventually landing on FSD v12.6 in January 2025 while AI4 vehicles moved to v13 and then v14. When Musk acknowledged in January 2025 that HW3 simply could not reach unsupervised operation, and alluded to a difficult hardware retrofit.
The near-term offering is more concrete. Tesla’s head of Autopilot Ashok Elluswamy confirmed on today’s call that a V14-lite will be coming to HW3 vehicles in late June, bringing all the V14 features currently running on AI4 hardware. That is a meaningful software update for owners who have been frozen at v12.6 for over a year, and it represents genuine effort to keep older hardware relevant. Unsupervised FSD for vehicles is now targeted for Q4 2026 at the earliest, with Musk describing it as a gradual, geography-limited rollout.
For HW3 owners, the over-the-air V14-lite update is welcomed, and the discounted trade-in path at least acknowledges an old obligation. What happens next with the trade-in pricing will define how this chapter ultimately gets written. If Tesla prices the hardware path fairly, acknowledges what early adopters are owed, and delivers V14-lite on the June timeline it committed to today, it has a real opportunity to convert one of the longest-running sore subjects among early adopters into a loyalty story.
Tesla pulls back the curtain on Cybercab mass production
Elon Musk talks Tesla Roadster’s future
