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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.
Elon Musk
Elon Musk’s X will start using a Tesla-like software update strategy
The initiative seems designed to accelerate updates to the social media platform, while maintaining maximum transparency.
Elon Musk’s social media platform X will adopt a Tesla-esque approach to software updates for its algorithm.
The initiative seems designed to accelerate updates to the social media platform, while maintaining maximum transparency.
X’s updates to its updates
As per Musk in a post on X, the social media company will be making a new algorithm to determine what organic and advertising posts are recommended to users. These updates would then be repeated every four weeks.
“We will make the new 𝕏 algorithm, including all code used to determine what organic and advertising posts are recommended to users, open source in 7 days. This will be repeated every 4 weeks, with comprehensive developer notes, to help you understand what changed,” Musk wrote in his post.
The initiative somewhat mirrors Tesla’s over-the-air update model, where vehicle software is regularly refined and pushed to users with detailed release notes. This should allow users to better understand the details of X’s every update and foster a healthy feedback loop for the social media platform.
xAI and X
X, formerly Twitter, has been acquired by Elon Musk’s artificial intelligence startup, xAI last year. Since then, xAI has seen a rapid rise in valuation. Following the company’s the company’s upsized $20 billion Series E funding round, estimates now suggest that xAI is worth tens about $230 to $235 billion. That’s several times larger than Tesla when Elon Musk received his controversial 2018 CEO Performance Award.
As per xAI, the Series E funding round attracted a diverse group of investors, including Valor Equity Partners, Stepstone Group, Fidelity Management & Research Company, Qatar Investment Authority, MGX, and Baron Capital Group, among others. Strategic partners NVIDIA and Cisco Investments also continued support for building the world’s largest GPU clusters.
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Tesla FSD Supervised wins MotorTrend’s Best Driver Assistance Award
The decision marks a notable reversal for the publication from prior years, with judges citing major real-world improvements that pushed Tesla’s latest FSD software ahead of every competing ADAS system.
Tesla’s Full Self-Driving (Supervised) system has been named the best driver-assistance technology on the market, earning top honors at the 2026 MotorTrend Best Tech Awards.
The decision marks a notable reversal for the publication from prior years, with judges citing major real-world improvements that pushed Tesla’s latest FSD software ahead of every competing ADAS system. And it wasn’t even close.
MotorTrend reverses course
MotorTrend awarded Tesla FSD (Supervised) its 2026 Best Tech Driver Assistance title after extensive testing of the latest v14 software. The publication acknowledged that it had previously criticized earlier versions of FSD for erratic behavior and near-miss incidents, ultimately favoring rivals such as GM’s Super Cruise in earlier evaluations.
According to MotorTrend, the newest iteration of FSD resolved many of those shortcomings. Testers said v14 showed far smoother behavior in complex urban scenarios, including unprotected left turns, traffic circles, emergency vehicles, and dense city streets. While the system still requires constant driver supervision, judges concluded that no other advanced driver-assistance system currently matches its breadth of capability.
Unlike rival systems that rely on combinations of cameras, radar, lidar, and mapped highways, Tesla’s FSD operates using a camera-only approach and is capable of driving on city streets, rural roads, and freeways. MotorTrend stated that pure utility, the ability to handle nearly all road types, ultimately separated FSD from competitors like Ford BlueCruise, GM Super Cruise, and BMW’s Highway Assistant.
High cost and high capability
MotorTrend also addressed FSD’s pricing, which remains significantly higher than rival systems. Tesla currently charges $8,000 for a one-time purchase or $99 per month for a subscription, compared with far lower upfront and subscription costs from other automakers. The publication noted that the premium is justified given FSD’s unmatched scope and continuous software evolution.
Safety remained a central focus of the evaluation. While testers reported collision-free operation over thousands of miles, they noted ongoing concerns around FSD’s configurable driving modes, including options that allow aggressive driving and speeds beyond posted limits. MotorTrend emphasized that, like all Level 2 systems, FSD still depends on a fully attentive human driver at all times.
Despite those caveats, the publication concluded that Tesla’s rapid software progress fundamentally reshaped the competitive landscape. For drivers seeking the most capable hands-on driver-assistance system available today, MotorTrend concluded Tesla FSD (Supervised) now stands alone at the top.
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Elon Musk’s Grokipedia surges to 5.6M articles, almost 79% of English Wikipedia
The explosive growth marks a major milestone for the AI-powered online encyclopedia, which was launched by Elon Musk’s xAI just months ago.
Elon Musk’s Grokipedia has grown to an impressive 5,615,201 articles as of today, closing in on 79% of the English Wikipedia’s current total of 7,119,376 articles.
The explosive growth marks a major milestone for the AI-powered online encyclopedia, which was launched by Elon Musk’s xAI just months ago. Needless to say, it would only be a matter of time before Grokipedia exceeds English Wikipedia in sheer volume.
Grokipedia’s rapid growth
xAI’s vision for Grokipedia emphasizes neutrality, while Grok’s reasoning capabilities allow for fast drafting and fact-checking. When Elon Musk announced the initiative in late September 2025, he noted that Grokipedia would be an improvement to Wikipedia because it would be designed to avoid bias.
At the time, Musk noted that Grokipedia “is a necessary step towards the xAI goal of understanding the Universe.”
Grokipedia was launched in late October, and while xAI was careful to list it only as Version 0.1 at the time, the online encyclopedia immediately earned praise. Wikipedia co-founder Larry Sanger highlighted the project’s innovative approach, noting how it leverages AI to fill knowledge gaps and enable rapid updates. Netizens also observed how Grokipedia tends to present articles in a more objective manner compared to Wikipedia, which is edited by humans.
Elon Musk’s ambitious plans
With 5,615,201 total articles, Grokipedia has now grown to almost 79% of English Wikipedia’s article base. This is incredibly quick, though Grokipedia remains text-only for now. xAI, for its part, has now updated the online encyclopedia’s iteration to v0.2.
Elon Musk has shared bold ideas for Grokipedia, including sending a record of the entire knowledge base to space as part of xAI’s mission to preserve and expand human understanding. At some point, Musk stated that Grokipedia will be renamed to Encyclopedia Galactica, and it will be sent to the cosmos.
“When Grokipedia is good enough (long way to go), we will change the name to Encyclopedia Galactica. It will be an open source distillation of all knowledge, including audio, images and video. Join xAI to help build the sci-fi version of the Library of Alexandria!” Musk wrote, adding in a later post that “Copies will be etched in stone and sent to the Moon, Mars and beyond. This time, it will not be lost.”