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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.
News
Tesla adds notable improvement to Dashcam feature
Tesla has added a notable improvement to its Dashcam feature after complaints from owners have pushed the company to make a drastic change.
Perhaps one of the biggest frustrations that Tesla owners have communicated regarding the Dashcam feature is the lack of ability to retain any more than 60 minutes of driving footage before it is overwritten.
It does not matter what size USB jump drive is plugged into the vehicle. 60 minutes is all it will hold until new footage takes over the old. This can cause some issues, especially if you were saving an impressive clip of Full Self-Driving or an incident on the road, which could be lost if new footage was recorded.
This has now been changed, as Tesla has shown in the Release Notes for an upcoming Software Update in China. It will likely expand to the U.S. market in the coming weeks, and was first noticed by NotaTeslaApp.
The release notes state:
“Dashcam Dynamic Recording Duration – The dashcam dynamically adjusts the recording duration based on the available storage capacity of the connected USB drive. For example, with a 128 GB USB drive, the maximum recording duration is approximately 3 hours; with a 1 TB or larger USB drive, it can reach up to 24 hours. This ensures that as much video as possible is retained for review before it gets overwritten.”
Tesla Adds Dynamic Recording
Instead of having a 60-minute cap, the new system will now go off the memory in the USB drive. This means with:
- 128 GB Jump Drive – Up to Three Hours of Rolling Footage
- 1TB Jump Drive – Up to 24 Hours of Rolling Footage
This is dependent on the amount of storage available on the jump drive, meaning that if there are other things saved on it, it will take away from the amount of footage that can be retained.
While the feature is just now making its way to employees in China, it will likely be at least several weeks before it makes its way to the U.S., but owners should definitely expect it in the coming months.
It will be a welcome feature, especially as there will now be more customization to the number of clips and their duration that can be stored.
Elon Musk
Will Tesla join the fold? Predicting a triple merger with SpaceX and xAI
With the news of a merger between SpaceX and xAI being confirmed earlier this week by CEO Elon Musk directly, the first moves of an umbrella company that combines all of the serial tech entrepreneur’s companies have been established.
The move aims to combine SpaceX’s prowess in launches with xAI’s expanding vision in artificial intelligence, as Musk has detailed the need for space-based data centers that will require massive amounts of energy to operate.
It has always been in the plans to bring Musk’s companies together under one umbrella.
“My companies are, surprisingly in some ways, trending toward convergence,” Musk said in November. With SpaceX and xAI moving together, many are questioning when Tesla will be next. Analysts believe it is a no-brainer.
SpaceX officially acquires xAI, merging rockets with AI expertise
Dan Ives of Wedbush wrote in a note earlier this week that there is a “growing chance” Tesla could be merged in some form with the new conglomeration over the next 12 to 18 months.
“In our view, there is a growing chance that Tesla will eventually be merged in some form into SpaceX/xAI over time. The viewis this growing AI ecosystem will focus on Space and Earth together… and Musk will look to combine forces,” Ives said.
Let’s take a look at the potential.
The Case for Synergies – Building the Ultimate AI Ecosystem
A triple merger would create a unified “Musk Trinity,” blending Tesla’s physical AI with Robotaxi, Optimus, and Full Self-Driving, SpaceX’s orbital infrastructure through Starlink and potential space-based computer, and xAI’s advanced models, including Grok.
This could accelerate real-world AI applications, more specifically, ones like using satellite networks for global autonomy, or even powering massive training through solar-optimized orbital data centers.
The FCC welcomes and now seeks comment on the SpaceX application for Orbital Data Centers.
The proposed system would serve as a first step towards becoming a Kardashev II-level civilization and serve other purposes, according to the applicant. pic.twitter.com/TDnUPuz9w7
— Brendan Carr (@BrendanCarrFCC) February 4, 2026
This would position the entity, which could ultimately be labeled “X,” as a leader in multiplanetary AI-native tech.
It would impact every level of Musk’s AI-based vision for the future, from passenger use to complex AI training models.
Financial and Structural Incentives — and Risks
xAI’s high cash burn rate is now backed by SpaceX’s massive valuation boost, and Tesla joining the merger would help the company gain access to private funding channels, avoiding dilution in a public-heavy structure.
The deal makes sense from a capital standpoint, as it is an advantage for each company in its own specific way, addressing specific needs.
Because xAI is spending money at an accelerating rate due to its massive compute needs, SpaceX provides a bit of a “lifeline” by redirecting its growing cash flows toward AI ambitions without the need for constant external fundraising.
Additionally, Tesla’s recent $2 billion investment in xAI also ties in, as its own heavy CapEx for Dojo supercomputers, Robotaxis, and Optimus could potentially be streamlined.
Musk’s stake in Tesla and SpaceX, after the xAI merger, is also uneven. His ownership in Tesla equates to about 13 percent, only increasing as he achieves each tranche of his most recent compensation package. Meanwhile, he owns about 43 percent of the private SpaceX.
A triple merger between the three companies could boost his ownership in the combined entity to around 26 percent. This would give Musk what he wants: stronger voting power and alignment across his ventures.
It could also be a potential facilitator in private-to-public transitions, as a reverse merger structure to take SpaceX public indirectly via Tesla could be used. This avoids any IPO scrutiny while accessing the public markets’ liquidity.
Timeline and Triggers for a Public Announcement
As previously mentioned, Ives believes a 12-18 month timeline is realistic, fueled by Musk’s repeated hints at convergence between his three companies. Additionally, the recent xAI investment by Tesla only points toward the increased potential for a conglomeration.
Of course, there is speculation that the merger could happen in the shorter term, before June 30 of this year, which is a legitimate possibility. While this possibility exists but remains at low probability, especially when driven by rapid AI/space momentum, longer horizons, like 2027 or later, allow for key milestones like Tesla’s Robotaxi rollout and Cybercab ramp-up, Optimus scaling, or regulatory clarity under a favorable administration.

Credit: Grok Imagine
The sequencing matters: SpaceX-xAI merger as “step one” toward a unified stack, with a potential SpaceX IPO setting a valuation benchmark before any Tesla tie-up.
Full triple convergence could follow if synergies prove out.
Prediction markets are also a reasonable thing to look at, just to get an idea of where people are putting their money. Polymarket, for example, sits at between a 12 and 24 percent chance that a Tesla-SpaceX merger is officially announced before June 30, 2026.
Looking Ahead
The SpaceX-xAI merger is not your typical corporate shuffle. Instead, it’s the clearest signal yet that Musk is architecting a unified “Muskonomy” where AI, space infrastructure, and real-world robotics converge to solve humanity’s biggest challenges.
Yet the path is fraught with execution risks that could turn this visionary upside into a major value trap. Valuation mismatches remain at the forefront of this skepticism: Tesla’s public multiples are unlike any company ever, with many believing they are “stretched.” On the other hand, SpaceX-xAI’s private “marked-to-muth” pricing hinges on unproven synergies and lofty projects, especially orbital data centers and all of the things Musk and Co. will have to figure out along the way.
Ultimately, the entire thing relies on a high-conviction bet on Musk’s ability to execute at scale. The bullish case is transformative: a vertically integrated AI-space-robotics giant accelerates humanity toward abundance and multi-planetary civilization faster than any siloed company could.
News
IM Motors co-CEO apologizes to Tesla China over FUD comments
Liu said later investigations showed the accident was not caused by a brake failure on the Tesla’s part, contrary to his initial comments.
Liu Tao, co-CEO of IM Motors, has publicly apologized to Tesla China for comments he made in 2022 suggesting a Tesla vehicle was defective following a fatal traffic accident in Chaozhou, China.
Liu said later investigations showed the accident was not caused by a brake failure on the Tesla’s part, contrary to his initial comments.
IM Motors co-CEO issues apology
Liu Tao posted a statement addressing remarks he made following a serious traffic accident in Chaozhou, Guangdong province, in November 2022, as noted in a Sina News report. Liu stated that based on limited public information at the time, he published a Weibo post suggesting a safety issue with the Tesla involved in the crash. The executive clarified that his initial comments were incorrect.
“On November 17, 2022, based on limited publicly available information, I posted a Weibo post regarding a major traffic accident that occurred in Chaozhou, suggesting that the Tesla product involved in the accident posed a safety hazard. Four hours later, I deleted the post. In May 2023, according to the traffic police’s accident liability determination and relevant forensic opinions, the Chaozhou accident was not caused by Tesla brake failure.
“The aforementioned findings and opinions regarding the investigation conclusions of the Chaozhou accident corrected the erroneous statements I made in my previous Weibo post, and I hereby clarify and correct them. I apologize for the negative impact my inappropriate remarks made before the facts were ascertained, which caused Tesla,” Liu said.


Investigation and court findings
The Chaozhou accident occurred in Raoping County in November 2022 and resulted in two deaths and three injuries. Video footage circulated online at the time showed a Tesla vehicle accelerating at high speed and colliding with multiple motorcycles and bicycles. Reports indicated the vehicle reached a speed of 198 kilometers per hour.
The incident drew widespread attention as the parties involved provided conflicting accounts and investigation details were released gradually. Media reports in early 2023 said investigation results had been completed, though the vehicle owner requested a re-investigation, delaying the issuance of a final liability determination.
The case resurfaced later in 2023 following a defamation lawsuit filed by Tesla China against a media outlet. According to a court judgment cited by Shanghai Securities News, forensic analysis determined that the fatal accident was unrelated to any malfunction on the Tesla’s braking or steering systems. The court also ruled that the media outlet must publish an apology, address the negative impact on Tesla China’s reputation, and pay a penalty of 30,000 yuan.