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Scientists create AI neural net that can unlock digital fingerprint-secured devices

Fingerprint scan. | Credit: RCPA

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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.

An overview of the DeepMasterPrint system. | Credit: IEEE

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.

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Real fingerprints on the left vs. DeepMasterPrint generated fingerprints on the right. | Credit: IEEE

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.

Accidental computer geek, fascinated by most history and the multiplanetary future on its way. Quite keen on the democratization of space. | It's pronounced day-sha, but I answer to almost any variation thereof.

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Tesla Model Y L gets biggest hint yet that it’s coming to the U.S.

Over the past week, a noticeable wave of American Tesla influencers descended on China and Australia, each posting in-depth YouTube reviews of the Model Y L within days of one another.

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Credit: Tesla China

The Tesla Model Y L is perhaps the most wanted vehicle in the company’s lineup in the United States, especially now that it is void of a true family vehicle with the removal of the Model X.

In China, Tesla currently offers a longer, more family-friendly version of the Model Y, known as the Model Y L, which is longer in terms of its wheelbase and larger in terms of interior space, making it the perfect option for those with a need for a tad more room than what the all-electric crossover offers in its Standard, Premium, and Performance trims.

However, there seems to be a hint that the Model Y L could be on its way to the United States. Over the past week, a noticeable wave of American Tesla influencers descended on China and Australia, each posting in-depth YouTube reviews of the Model Y L within days of one another:

The timing has sparked some intense speculation as to whether Tesla is quietly preparing to bring the long-wheelbase, three-row family SUV to North America after months of requests from fans.

The Model Y L stretches the wheelbase by about five inches compared to the standard Model Y.

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This delivers dramatically more rear legroom, optional captain’s chairs in the second row, and a true six- or seven-seat configuration ideal for growing families. Reviewers praise its refined ride, upgraded interior features like a rear touchscreen and premium audio, and competitive range—up to roughly 466 miles in some configurations.

Many observers see the coordinated influencer trip as more than a coincidence. Tesla China appears to have hosted the group, possibly tied to the Beijing Auto Show, giving U.S.-focused creators early access to hands-on footage aimed squarely at North American audiences.

Tesla Model Y lineup expansion signals an uncomfortable reality for consumers

Tesla watchers are quick to point out this isn’t the first time such a pattern has emerged.

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Just months earlier, American influencers were similarly invited to China to test-drive the refreshed Model Y Performance. Those videos dropped in the lead-up to the variant’s U.S. rollout, generating exactly the kind of pre-launch hype that helped smooth its September arrival in American showrooms.

The parallel is obviously hard to ignore, as Tesla has used overseas influencer trips before as a low-key way to build anticipation without formal announcements. With the Model Y L potentially hitting the U.S. market late this year, according to CEO Elon Musk, the timing would make sense.

Tesla Model Y L might not come to the U.S., and it’s a missed opportunity

Of course, it could still be coincidental. Tesla regularly invites creators to its Shanghai factory and events for broader promotional purposes, and the Model Y L has been on sale in China for some time. No official word has come from Tesla or Elon Musk about U.S. availability, pricing, or timing.

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Import tariffs, regulatory hurdles, and production priorities at Fremont or the new Mexican Gigafactory could still delay or alter any stateside plans.

Even so, the buzz is real. U.S. families have long asked for a more spacious, three-row Tesla SUV that doesn’t require stepping up to the larger Model X.

If the influencer campaign is any indication, the Model Y L—or a close North American cousin—could finally answer that call. For now, American Tesla fans are watching closely and wondering whether this latest China trip is just good content… or the opening act for something much bigger stateside.

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Tesla begins probing owners on FSD’s navigation errors with small but mighty change

Previously lumped under “Other,” these incidents made it harder for Tesla’s AI team to isolate and prioritize map-related issues in their reinforcement learning models. There was a lot of disagreement on how certain interventions should be reported.

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Tesla has started probing owners on how often its Full Self-Driving suite has Navigation errors with a small but mighty change last night.

In its latest Software Update, which is Version 2026.2.9.9 featuring Full Self-Driving (Supervised) v14.3.2, Tesla has introduced a targeted improvement to how owners will report interventions.

With the initial rollout of v14.3.2, Tesla introduced a new Intervention Menu that appears when a disengagement occurs. It allowed owners to choose from four different categories: Preference, Comfort, Critical, or Other.

Tesla has voided the Other option and replaced it with a new “Navigation” choice, which seems much more ideal given the complaints owners have had about navigation. This seemingly minor UI tweak, rolled out widely in recent days, marks another step in Tesla’s ongoing effort to refine its autonomous driving stack through precise, crowdsourced data.

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Tesla made this change in direct response to longstanding community feedback. For years, FSD users have noted that navigation errors—such as incorrect speed limits, suboptimal routes, or directing the vehicle to a building’s rear entrance instead of the main one—frequently force interventions.

Previously lumped under “Other,” these incidents made it harder for Tesla’s AI team to isolate and prioritize map-related issues in their reinforcement learning models. There was a lot of disagreement on how certain interventions should be reported:

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By adding a dedicated “Navigation” label, the company can now tag disengagements more accurately, feeding cleaner data into its neural networks. This supports faster iteration on routing algorithms, map accuracy, and intent-aware navigation.

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Community consensus around Tesla’s navigation system has been consistent and candid. While the end-to-end AI driving behavior in v14.x earns widespread acclaim for smoothness and safety, navigation remains FSD’s clearest Achilles’ heel.

Owners frequently cite outdated map data, failure to learn from repeated corrections, and routing decisions that feel less intuitive than Google Maps or Apple Maps. Common complaints include phantom speed-limit changes, inefficient local roads, and poor point-of-interest handling.

Tesla Summon got insanely good in FSD v14.3.2 — Navigation? Not so much

Many drivers report intervening on navigation far more often than on core driving maneuvers, with some estimating it accounts for the majority of disengagements outside of edge cases.

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Long-term users note that the same mapping glitches persist across years and software versions, despite thousands of collective miles of feedback. Yet the addition of the “Navigation” option has been met with optimism. It signals Tesla’s commitment to data-driven progress and suggests navigation improvements could arrive sooner.

For a community that already logs millions of FSD miles monthly, this small change could unlock meaningful gains in reliability and user trust—potentially accelerating the path to unsupervised autonomy.

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Tesla expands Robotaxi in a way that was long anticipated

Instead, it has to do with the consumer base it offers Robotaxi to, because it has not offered it to everyone in the past.

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Credit: Grok Imagine

Tesla has expanded Robotaxi in a way that was long anticipated, and it does not have to do with a new, larger geofence in a city where it already offered its partially autonomous ride-hailing suite, or a new city altogether.

Instead, it has to do with the consumer base it offers Robotaxi to, because it has not offered it to everyone in the past.

Tesla has taken a major step forward in its autonomous ride-hailing ambitions with the official launch of the Tesla Robotaxi app for Android users. Released on the Google Play Store on April 24. Titled simply “Tesla Robotaxi,” the app is now available to download directly from Tesla.

This rollout fulfills a long-anticipated expansion that opens the service to hundreds of millions of Android smartphone users who were previously unable to access it on iOS alone.

The app delivers a streamlined, driverless ride experience powered by Tesla’s automated driving technology.

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Users sign in with a Tesla Account, view the current service area map within the app, enter a destination, and receive an estimated fare and arrival time before confirming the ride. When a Model Y from the Robotaxi fleet arrives, riders confirm the license plate, enter the vehicle, fasten their seatbelt, and tap “Start Ride” on either the app or the vehicle’s touchscreen.

During the trip, passengers have access to all the same controls that iOS users do, and can adjust climate settings, seat positions, and music while tracking progress on an in-app map. The interface also allows drop-off changes or support requests if needed. After the ride, users exit, close the doors, and submit feedback.

This Android availability directly broadens the rider base for Robotaxi in its initial service areas. Unfortunately, Android users are used to being subject to delayed launches of new features available to Tesla owners.

By removing the iOS-only barrier, Tesla instantly expands the addressable market, enabling far more people to summon and use the autonomous vehicles already operating on public roads.

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The move is a foundational requirement for scaling ride volume and gathering the real-world data needed to refine the unsupervised Full Self-Driving system that powers every trip.

For the Robotaxi program itself, the launch signals steady operational progress. It prepares the service for higher utilization rates as the fleet grows and supports the transition from limited early deployments to a more robust network.

Tesla expands Unsupervised Robotaxi service to two new cities

Tesla has indicated that users outside current service areas can sign up at the company’s website for future notifications, pointing to a deliberate, phased geographic rollout.

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Looking ahead, the company plans to incorporate Cybercab vehicles to increase fleet capacity and efficiency while continuing to expand service territories. With the Android app now live, Tesla has removed a key adoption hurdle and positioned Robotaxi for the next phase of growth in autonomous urban transportation.

The infrastructure is now in place to support significantly larger rider demand as production and deployment accelerate.

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