News
Tesla patents virtualization and machine learning software to improve FSD
Tesla has applied for a set of patents that are set to significantly improve virtualization, recognition, and Full Self Driving overall.
Tesla has worked tirelessly to improve full self-driving technology in the first two months of the year. Most recently, Tesla pushed its most significant improvement to employees, v11.3. Still, with new patented technology, the software is set to continue to improve dramatically this year. The two patents, focusing on virtualization and machine learning, appeared in the U.S. Patent Office database late last week.
The first patent, “Vision-Based Machine Learning Model for Autonomous Driving with Adjustable Virtual Camera,” is likely simply a reworking of a previous system but changed to fit Tesla’s new visual-only autonomous driving system. The second patent, “Vision-Based Machine Learning Model for Aggregation of Static Objects and Systems for Autonomous Driving,” focuses more on improving the virtualization seen on screen while in the vehicle.
The first patent’s abstract describes a system that looks similar to the one already available in Tesla vehicles but has been adapted to remove non-visual sensors. However, it does include an added “adjustable virtual camera,” potentially indicating that Tesla is working to give drivers more control of looking out of their car with the camera system or improved virtualization interaction.
“Systems and methods for a vision-based machine learning model for autonomous driving with adjustable virtual camera. An example method includes obtaining images from a multitude of image sensors positioned about a vehicle. Features associated with the images are determined, with the features being output based on a forward pass through a first portion of a machine learning model. The features are projected into a vector space associated with a virtual camera at a particular height. The projected features are aggregated with other projected features associated with prior images.”
The second, significantly more extensive patent is described in its abstract, focusing on the “aggregation of static objects” by the vehicle:
“Systems and methods for a vision-based machine learning model for aggregation of static objects and systems for autonomous driving. An example method includes obtaining images from image sensors positioned about a vehicle. Features associated with the images are determined, with the features being output based on a forward pass through a machine learning model. The features are projected into a vector space associated with a birds-eye view based on the machine learning model.”
If anything, the new patents from Tesla show just how dedicated it is to its visual-only system. Nowhere in either of the patents does the automaker address other sensor inputs, which seems to line up with recent discoveries showing upcoming vehicles without ultrasonic sensors.
Further, with Tesla’s increasing focus on making vehicles more AI capable, implementing improved machine learning also matches its design goals.
It remains unclear whether these improvements have been implemented in upcoming software versions or have already been placed in cars via recent software updates. Still, they nonetheless indicate that the company is making continuous progress in its pursuit.
As more and more automakers enter the autonomous driving competition, Tesla’s lead becomes ever more apparent. And while many have mocked the company for its dedication to AI over just vehicles, that investment is proving to be a fantastic one. Hopefully, it will result in an increasingly better Tesla driving experience in the coming years.
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News
Tesla looks to upgrade Matrix Headlights with new features
According to the update, Tesla will work on improving the headlights when coming into contact with highly reflective objects, including road signs, traffic signs, and street lights. Additionally, pixel-level dimming will happen in two stages, whereas it currently performs with just one, meaning on or off.
Tesla is looking to upgrade its Matrix Headlights, a unique and high-tech feature that is available on several of its vehicles. The headlights aim to maximize visibility for Tesla drivers while being considerate of oncoming traffic.
The Matrix Headlights Tesla offers utilize dimming of individual light pixels to ensure that visibility stays high for those behind the wheel, while also being considerate of other cars by decreasing the brightness in areas where other cars are traveling.
Here’s what they look like in action:
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- Credit: u/ObjectiveScratch | Reddit
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- Credit: u/ObjectiveScratch | Reddit
As you can see, the Matrix headlight system intentionally dims the area where oncoming cars would be impacted by high beams. This keeps visibility at a maximum for everyone on the road, including those who could be hit with bright lights in their eyes.
There are still a handful of complaints from owners, however, but Tesla appears to be looking to resolve these with the coming updates in a Software Version that is currently labeled 2026.2.xxx. The coding was spotted by X user BERKANT:
🚨 Tesla is quietly upgrading Matrix headlights.
Software https://t.co/pXEklQiXSq reveals a hidden feature:
matrix_two_stage_reflection_dip
This is a major step beyond current adaptive high beams.
What it means:
• The car detects highly reflective objects
Road signs,… pic.twitter.com/m5UpQJFA2n— BERKANT (@Tesla_NL_TR) February 24, 2026
According to the update, Tesla will work on improving the headlights when coming into contact with highly reflective objects, including road signs, traffic signs, and street lights. Additionally, pixel-level dimming will happen in two stages, whereas it currently performs with just one, meaning on or off.
Finally, the new system will prevent the high beams from glaring back at the driver. The system is made to dim when it recognizes oncoming cars, but not necessarily objects that could produce glaring issues back at the driver.
Tesla’s revolutionary Matrix headlights are coming to the U.S.
This upgrade is software-focused, so there will not need to be any physical changes or upgrades made to Tesla vehicles that utilize the Matrix headlights currently.
Elon Musk
xAI’s Grok approved for Pentagon classified systems: report
Under the agreement, Grok can be deployed in systems handling classified intelligence analysis, weapons development, and battlefield operations.
Elon Musk’s xAI has signed an agreement with the United States Department of Defense (DoD) to allow Grok to be used in classified military systems.
Previously, Anthropic’s Claude had been the only AI system approved for the most sensitive military work, but a dispute over usage safeguards has reportedly prompted the Pentagon to broaden its options, as noted in a report from Axios.
Under the agreement, Grok can be deployed in systems handling classified intelligence analysis, weapons development, and battlefield operations.
The publication reported that xAI agreed to the Pentagon’s requirement that its technology be usable for “all lawful purposes,” a standard Anthropic has reportedly resisted due to alleged ethical restrictions tied to mass surveillance and autonomous weapons use.
Defense Secretary Pete Hegseth is scheduled to meet with Anthropic CEO Dario Amodei in what sources expect to be a tense meeting, with the publication hinting that the Pentagon could designate Anthropic a “supply chain risk” if the company does not lift its safeguards.
Axios stated that replacing Claude fully might be technically challenging even if xAI or other alternative AI systems take its place. That being said, other AI systems are already in use by the DoD.
Grok already operates in the Pentagon’s unclassified systems alongside Google’s Gemini and OpenAI’s ChatGPT. Google is reportedly close to an agreement that will result in Gemini being used for classified use, while OpenAI’s progress toward classified deployment is described as slower but still feasible.
The publication noted that the Pentagon continues talks with several AI companies as it prepares for potential changes in classified AI sourcing.
Elon Musk
Elon Musk denies Starlink’s price cuts are due to Amazon Kuiper
“This has nothing to do with Kuiper, we’re just trying to make Starlink more affordable to a broader audience,” Musk wrote in a post on X.
Elon Musk has pushed back on claims that Starlink’s recent price reductions are tied to Amazon’s Kuiper project.
In a post on X, Musk responded directly to a report suggesting that Starlink was cutting prices and offering free hardware to partners ahead of a planned IPO and increased competition from Kuiper.
“This has nothing to do with Kuiper, we’re just trying to make Starlink more affordable to a broader audience,” Musk wrote in a post on X. “The lower the cost, the more Starlink can be used by people who don’t have much money, especially in the developing world.”
The speculation originated from a post summarizing a report from The Information, which ran with the headline “SpaceX’s Starlink Makes Land Grab as Amazon Threat Looms.” The report stated that SpaceX is aggressively cutting prices and giving free hardware to distribution partners, which was interpreted as a reaction to Amazon’s Kuiper’s upcoming rollout and possible IPO.
In a way, Musk’s comments could be quite accurate considering Starlink’s current scale. The constellation currently has more than 9,700 satellites in operation today, making it by far the largest satellite broadband network in operation. It has also managed to grow its user base to 10 million active customers across more than 150 countries worldwide.
Amazon’s Kuiper, by comparison, has launched approximately 211 satellites to date, as per data from SatelliteMap.Space, some of which were launched by SpaceX’s Falcon 9 rocket. Starlink surpassed that number in early January 2020, during the early buildout of its first-generation network.
Lower pricing also aligns with Starlink’s broader expansion strategy. SpaceX continues to deploy satellites at a rapid pace using Falcon 9, and future launches aboard Starship are expected to significantly accelerate the constellation’s growth. A larger network improves capacity and global coverage, which can support a broader customer base.
In that context, price reductions can be viewed as a way to match expanding supply with growing demand. Musk’s companies have historically used aggressive pricing strategies to drive adoption at scale, particularly when vertical integration allows costs to decline over time.
Tesla looks to upgrade Matrix Headlights with new features
xAI’s Grok approved for Pentagon classified systems: report
