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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 adds awesome new driving feature to Model Y

Tesla is rolling out a new “Comfort Braking” feature with Software Update 2026.8. The feature is exclusive to the new Model Y, and is currently unavailable for any other vehicle in the Tesla lineup.

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Credit: Tesla

Tesla is adding an awesome new driving feature to Model Y vehicles, effective on Juniper-updated models considered model year 2026 or newer.

Tesla is rolling out a new “Comfort Braking” feature with Software Update 2026.8. The feature is exclusive to the new Model Y, and is currently unavailable for any other vehicle in the Tesla lineup.

Tesla writes in the release notes for the feature:

“Your Tesla now provides a smoother feel as you come to a complete stop during routine braking.”

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Interestingly, we’re not too sure what catalyzed Tesla to try to improve braking smoothness, because it hasn’t seemed overly abrupt or rough from my perspective. Although the brake pedal in my Model Y is rarely used due to Regenerative Braking, it seems Tesla wanted to try to make the ride comfort even smoother for owners.

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There is always room for improvement, though, and it seems that there is a way to make braking smoother for passengers while the vehicle is coming to a stop.

This is far from the first time Tesla has attempted to improve its ride comfort through Over-the-Air updates, as it has rolled out updates to improve regenerative braking performance, handling while using Full Self-Driving, improvements to Steer-by-Wire to Cybertruck, and even recent releases that have combatted Active Road Noise.

Tesla set to activate long-awaited Cybertruck feature

Tesla holds a unique ability to change the functionality of its vehicles through software updates, which have come in handy for many things, including remedying certain recalls and shipping new features to the Full Self-Driving suite.

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Tesla seems to have the most seamless OTA processes, as many automakers have the ability to ship improvements through a simple software update.

We’re really excited to test the update, so when we get an opportunity to try out Comfort Braking when it makes it to our Model Y.

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Tesla finally brings a Robotaxi update that Android users will love

The breakdown of the software version shows that Tesla is actively developing an Android-compatible version of the Robotaxi app, and the company is developing Live Activities for Android.

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Credit: Grok

Tesla is finally bringing an update of its Robotaxi platform that Android users will love — mostly because it seems like they will finally be able to use the ride-hailing platform that the company has had active since last June.

Based on a decompile of software version 26.2.0 of the Robotaxi app, Tesla looks to be ready to roll out access to Android users.

According to the breakdown, performed by Tesla App Updates, the company is preparing to roll out an Android version of the app as it is developing several features for that operating system.

The breakdown of the software version shows that Tesla is actively developing an Android-compatible version of the Robotaxi app, and the company is developing Live Activities for Android:

“Strings like notification_channel_robotaxid_trip_name and android_native_alicorn_eta_text show exactly how Tesla plans to replicate the iOS Live Activities experience. Instead of standard push alerts, Android users are getting a persistent, dynamically updating notification channel.”

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This is a big step forward for several reasons. From a face-value perspective, Tesla is finally ready to offer Robotaxi to Android users.

The company has routinely prioritized Apple releases because there is a higher concentration of iPhone users in its ownership base. Additionally, the development process for Apple is simply less laborious.

Tesla is working to increase Android capabilities in its vehicles

Secondly, the Robotaxi rollout has been a typical example of “slowly then all at once.”

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Tesla initially released Robotaxi access to a handful of media members and influencers. Eventually, it was expanded to more users, so that anyone using an iOS device could download the app and hail a semi-autonomous ride in Austin or the Bay Area.

Opening up the user base to Android users may show that Tesla is preparing to allow even more users to utilize its Robotaxi platform, and although it seems to be a few months away from only offering fully autonomous rides to anyone with app access, the expansion of the user base to an entirely different user base definitely seems like its a step in the right direction.

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Lucid unveils Lunar Robotaxi in bid to challenge Tesla’s Cybercab in the autonomous ride hailing race

Lucid’s Lunar robotaxi is gunning for Tesla’s Cybercab in the autonomous ride hailing race

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Lucid Lunar robotaxi concept [Credit: Rendering by TESLARATI]

Lucid Group pulled back the curtain on its purpose-built autonomous robotaxi platform dubbed the Lunar Concept. Announced at its New York investor day event, Lunar is arguably the company’s most ambitious concept yet, and a direct line of sight toward the autonomous ride haling market that Tesla looks to control.

At Lucid Investor Day 2026, the company introduced Lunar, a purpose-built robotaxi concept based on the Midsize platform.

A comparison to Tesla’s Cybercab is unavoidable. The concept of a Tesla robotaxi was first introduced by Elon Musk back in April 2019 during an event dubbed “Autonomy Day,” where he envisioned a network of self-driving Tesla vehicles transporting passengers while not in use by their owners. That vision took another major step in October 2024 when, Musk unveiled the Cybercab at the Tesla “We, Robot” event held at Warner Bros. Studios in Burbank, California, where 20 concept Cybercabs autonomously drove around the studio lot giving rides to attendees.

Tesla unveils the Robovan at ‘We, Robot’ event

Fast forward to today, and Tesla’s ambitions are finally materializing, but not without friction. As we recently reported, the Cybercab is being spotted with increasing frequency on public roads and across the grounds of Gigafactory Texas, suggesting that the company’s road testing and validation program is ramping meaningfully ahead of mass production. Tesla already operates a small scale robotaxi service in Austin using supervised Model Ys, but the Cybercab is designed from the ground up for high-volume, low-cost production, with Musk stating an eventual goal of producing one vehicle every 10 seconds.

At Lucid Investor Day 2026, the company introduced Lunar, a purpose-built robotaxi concept based on the Midsize platform.

Into this landscape steps Lucid’s Lunar. Built on the company’s all-new Midsize EV platform, which will also underpin consumer SUVs starting below $50,000. The Lunar mirrors the Cybercab’s core philosophy of having two seats, no driver controls, and a focus on fleet economics. The platform introduces Lucid’s redesigned Atlas electric drive unit, engineered to be smaller, lighter, and cheaper to manufacture at scale.

Unlike Tesla’s strategy of building its own ride hailing network from scratch, Lucid is partnering with Uber. The companies are said to be in advanced discussions to deploy Midsize platform vehicles at large scale, with Uber CEO Dara Khosrowshahi publicly backing Lucid’s engineering credentials and autonomous-ready architecture.

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In the investor day event, Lucid also outlined a recurring software revenue model, with an in-vehicle AI assistant and monthly autonomous driving subscriptions priced between $69 and $199. This can be seen as a nod to the software revenue stream that Tesla has long championed with its Full Self-Driving subscription.

Tesla’s Cybercab is targeting a price point below $30k and with operating costs as low as 20 cents per mile. But with regulatory hurdles still ahead, the window for competition is open. Lucid’s Lunar may not have a launch date yet, but it arrives at a pivotal moment, and when the robotaxi race is no longer viewed as hypothetical. Rather, every serious EV player needs to come to bat on the same plate that Tesla has had countless practice swings on over the last seven years.

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