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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.

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.

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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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Elon Musk

Elon Musk proposes Grok 5 vs world’s best League of Legends team match

Musk’s proposal has received positive reception from professional players and Riot Games alike.

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UK Government, CC BY 2.0 , via Wikimedia Commons

Elon Musk has proposed a high-profile gaming challenge for xAI’s upcoming Grok 5. As per Musk, it would be interesting to see if the large language model could beat the world’ best human League of Legends team with specific constraints.

Musk’s proposal has received positive reception from professional players and Riot Games alike, suggesting that the exciting exhibition match might indeed happen. 

Musk outlines restrictions for Grok

In his post on X, Musk detailed constraints to keep the match competitive, including limiting Grok to human-level reaction times, human-speed clicking, and viewing the game only through a camera feed with standard 20/20 vision. The idea quickly circulated across the esports community, drawing commentary from former pros and AI researchers, as noted in a Dexerto report.

Former League pro Eugene “Pobelter” Park expressed enthusiasm, offering to help Musk’s team and noting the unique comparison to past AI-versus-human breakthroughs, such as OpenAI’s Dota 2 bots. AI researcher Oriol Vinyals, who previously reached Grandmaster rank in StarCraft, suggested testing Grok in RTS gameplay as well. 

Musk welcomed the idea, even responding positively to Vinyals’ comment that it would be nice to see Optimus operate the mouse and keyboard.

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Pros debate Grok’s chances, T1 and Riot show interest

Reactions weren’t universally optimistic. Former professional mid-laner Joedat “Voyboy” Esfahani argued that even with Grok’s rapid learning capabilities, League of Legends requires deep synergy, game-state interpretation, and team coordination that may be difficult for AI to master at top competitive levels. Yiliang “Doublelift” Peng was similarly skeptical, publicly stating he doubted Grok could beat T1, or even himself, and jokingly promised to shave his head if Grok managed to win.

T1, however, embraced the proposal, responding with a GIF of Faker and the message “We are ready,” signaling their willingness to participate. Riot Games itself also reacted, with co-founder Marc Merrill replying to Musk with “let’s discuss.” Needless to say, it appears that Riot Games in onboard with the idea.

Though no match has been confirmed, interest from players, teams, and Riot suggests the concept could materialize into a landmark AI-versus-human matchup, potentially becoming one of the most viewed League of Legends events in history. The fact that Grok 5 will be constrained to human limits would definitely add an interesting dimension to the matchup, as it could truly demonstrate how human-like the large language model could be like in real-time scenarios.

Tesla has passed a key milestone, and it was one that CEO Elon Musk initially mentioned more than nine years ago when he published Master Plan, Part Deux. 

As per Tesla China in a post on its official Weibo account, the company’s Autopilot system has accumulated over 10 billion kilometers of real-world driving experience.

Tesla China’s subtle, but huge announcement

In its Weibo post, Tesla China announced that the company’s Autopilot system has accumulated 10 billion kilometers of driving experience. “In this respect, Tesla vehicles equipped with Autopilot technology can be considered to have the world’s most experienced and seasoned driver.” 

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Tesla AI’s handle on Weibo also highlighted a key advantage of the company’s self-driving system. “It will never drive under the influence of alcohol, be distracted, or be fatigued,” the team wrote. “We believe that advancements in Autopilot technology will save more lives.”

Tesla China did not clarify exactly what it meant by “Autopilot” in its Weibo post, though the company’s intense focus on FSD over the past years suggests that the term includes miles that were driven by FSD (Beta) and Full Self-Driving (Supervised). Either way, 10 billion cumulative miles of real-world data is something that few, if any, competitors could compete with.

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Credit: Tesla China/Weibo

Elon Musk’s 10-billion-km estimate, way back in 2016

When Elon Musk published Master Plan Part Deux, he outlined his vision for the company’s autonomous driving system. At the time, Autopilot was still very new, though Musk was already envisioning how the system could get regulatory approval worldwide. He estimated that worldwide regulatory approval will probably require around 10 billion miles of real-world driving data, which was an impossible-sounding amount at the time. 

“Even once the software is highly refined and far better than the average human driver, there will still be a significant time gap, varying widely by jurisdiction, before true self-driving is approved by regulators. We expect that worldwide regulatory approval will require something on the order of 6 billion miles (10 billion km). Current fleet learning is happening at just over 3 million miles (5 million km) per day,” Musk wrote. 

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It’s quite interesting but Tesla is indeed getting regulatory approval for FSD (Supervised) at a steady pace today, at a time when 10 billion miles of data has been achieved. The system has been active in the United States and has since been rolled out to other countries such as Australia, New Zealand, China, and, more recently, South Korea. Expectations are high that Tesla could secure FSD approval in Europe sometime next year as well. 

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Elon Musk’s Boring Company reveals Prufrock TBM’s most disruptive feature

As it turns out, the tunneling startup, similar to other Elon Musk-backed ventures, is also dead serious about pursuing reusability.

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The Boring Company has quietly revealed one of its tunnel boring machines’ (TBMs) most underrated feature. As it turns out, the tunneling startup, similar to other Elon Musk-backed ventures, is also dead serious about pursuing reusability.

Prufrock 5 leaves the factory

The Boring Company is arguably the quietest venture currently backed by Elon Musk, inspiring far fewer headlines than his other, more high-profile companies such as Tesla, SpaceX, and xAI. Still, the Boring Company’s mission is ambitious, as it is a company designed to solve the problem of congestion in cities.

To accomplish this, the Boring Company would need to develop tunnel boring machines that could dig incredibly quickly. To this end, the startup has designed Prufrock, an all-electric TBM that’s designed to eventually be fast enough as an everyday garden snail. Among TBMs, such a speed would be revolutionary. 

The startup has taken a step towards this recently, when The Boring Company posted a photo of Prufrock-5 coming out of its Bastrop, Texas facility. “On a rainy day in Bastrop, Prufrock-5 has left the factory. Will begin tunneling by December 1.  Hoping for a step function increase in speed,” the Boring Company wrote.

Prufrock’s quiet disruption

Interestingly enough, the Boring Company also mentioned a key feature of its Prufrock machines that makes them significantly more sustainable and reusable than conventional TBMs. As per a user on X, standard tunnel boring machines are often left underground at the conclusion of a project because retrieving them is usually more expensive and impractical than abandoning them in the location. 

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As per the Boring Company, however, this is not the case for its Prufrock machines, as they are retrieved, upgraded, and deployed again with improvements. “All Prufrocks are reused, usually with upgrades between launches. Prufrock-1 has now dug six tunnels,” the Boring Company wrote in its reply on X.

The Boring Company’s reply is quite exciting as it suggests that the TBMs from the tunneling startup could eventually be as reusable as SpaceX’s boosters. This is on brand for an Elon Musk-backed venture, of course, though the Boring Company’s disruption is a bit more underground. 

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Tesla accused of infringing robotics patents in new lawsuit

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tesla store in New York City
Credit: Tesla

Tesla is being accused of infringing robotics patents by a company called Perrone Robotics, which is based out of Charlottesville, Virginia.

The suit was filed in Alexandria, Virginia, and accuses Tesla of knowingly infringing upon five patents related to robotics systems for self-driving vehicles.

The company said its founder, Paul Perrone, developed general-purpose robotics operating systems for individual robots and automated devices.

Perrone Robotics claims that all Tesla vehicles utilizing the company’s Autopilot suite within the last six years infringe the five patents, according to a report from Reuters.

Tesla’s new Safety Report shows Autopilot is nine times safer than humans

One patent was something the company attempted to sell to Tesla back in 2017. The five patents cover a “General Purpose Operating System for Robotics,” otherwise known as GPROS.

The GPROS suite includes extensions for autonomous vehicle controls, path planning, and sensor fusion. One key patent, U.S. 10,331,136, was explicitly offered to Tesla by Perrone back in 2017, but the company rejected it.

The suit aims to halt any further infringements and seeks unspecified damages.

This is far from the first suit Tesla has been involved in, including one from his year with Perceptive Automata LLC, which accused Tesla of infringing on AI models to interpret pedestrian/cyclist intent via cameras without licensing. Tesla appeared in court in August, but its motion to dismiss was partially denied earlier this month.

Tesla also settled a suit with Arsus LLC, which accused Autopilot’s electronic stability features of infringing on rollover prevention tech. Tesla won via an inter partes review in September.

Most of these cases involve non-practicing entities or startups asserting broad autonomous vehicle patents against Tesla’s rapid iteration.

Tesla typically counters with those inter partes reviews, claiming invalidity. Tesla has successfully defended about 70 percent of the autonomous vehicle lawsuits it has been involved in since 2020, but settlements are common to avoid discovery costs.

The case is Perrone Robotics Inc v Tesla Inc, U.S. District Court, Eastern District of Virginia, No. 25-02156. Tesla has not yet listed an attorney for the case, according to the report.

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