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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.
What do you think of the article? Do you have any comments, questions, or concerns? Shoot me an email at william@teslarati.com. You can also reach me on Twitter @WilliamWritin. If you have news tips, email us at tips@teslarati.com!
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SpaceX just locked up a NASA record no other U.S. spacecraft can touch
SpaceX’s Crew-13 Dragon reached the ISS in under eight hours, and NASA confirmed a record.
SpaceX now owns every spot on the list of the five fastest trips a U.S. spacecraft has ever made to the International Space Station, and its newest entry beat the old mark by more than four hours.
Crew Dragon Grace docked to the forward port of the station’s Harmony module at 7:05 p.m. ET on October 1, just 7 hours and 55 minutes after lifting off from Space Launch Complex 40 at Cape Canaveral. NASA confirmed the milestone in a space station blog update, writing that the flight “marked the fastest launch‑to‑docking of a U.S. spacecraft in the history of the International Space Station.”
The previous U.S. record also belonged to Dragon. SpaceX’s uncrewed CRS-31 cargo mission reached the station in a little over 12 hours in November 2024. The fastest crewed trip before last week was Crew-11, which took 14 hours and 43 minutes in August 2025, according to Space.com.
A post that Elon Musk reposted on Monday filled out the rest of the ranking. Behind Crew-13, CRS-31 and Crew-11 sit Axiom’s Ax-2 mission at 15 hours and 35 minutes and NASA’s Crew-4 at 15 hours and 44 minutes. All five flew on Dragon.
SpaceX turned a heralding moment for Starship into its greatest
Crew-13 carried NASA astronauts Jessica Watkins and Luke Delaney, Canadian Space Agency astronaut Joshua Kutryk, and Roscosmos cosmonaut Sergey Teteryatnikov. NASA had projected a docking around 8 p.m. ET, as Teslarati reported the day before launch, and Dragon arrived nearly an hour early. Our launch day coverage noted that the flight was lined up to be the quickest Crew Dragon transit yet.
The speed came from timing more than hardware. SpaceX’s Julianna Scheiman said the station “was in an opportune spot in space,” which let Dragon start closing the gap almost immediately after reaching orbit. “This is close to the fastest it could be,” she added. Most Crew Dragon flights still take close to a day, using a series of Draco thruster burns to raise and phase their orbit before arrival.
Dragon’s next job at the station is a departure. NASA said Monday it is targeting 8:05 a.m. ET on Wednesday, October 7, for Crew-12 to undock, setting up a splashdown off the coast of California around 11:34 a.m. on Thursday. Clearing that port makes room for CRS-35, a cargo Dragon carrying the final set of iROSA solar arrays.
Dragon remains NASA’s only operational ride to the station while Boeing’s Starliner stays grounded, and the agency recently added Crew-15, Crew-16 and Crew-17 to SpaceX’s contract in a $946 million modification.
Elon Musk has acknowledged that early discussions with Taiwan Semiconductor Manufacturing Company (TSMC) could bring the company into his ambitious Terafab semiconductor project, signaling a possible partnership with the world’s leading contract chipmaker.
Musk confirmed that early talks are underway, but as of right now, they are “just discussions.” There is no confirmation of a deal nor dismissal of the possibility of one, leaving open the prospect of one of the largest advanced-chip collaborations under discussion in the U.S.
@wholemars Just discussions, but something may come of it
— Elon Musk (@elonmusk) October 3, 2026
The report that speculated on potential discussions between Terafab and TSMC comes from Tim Culpan, who outlined a few ways the collaboration could operate. One is TSMC using the project as an “anchor customer” for future facilities in Texas, potentially contributing process expertise, operational know-how, or capacity while Terafab provides capital, long-term purchase commitments, or both.
Tesla and SpaceX jointly developed the Terafab project, with Intel already participating on the tech side. Elon Musk announced the project in March, and it intends to produce more than one terawatt of AI compute capacity annually once fully built.
Company statements place the first phase at approximately $16.8 billion in cost, with later filings pointing to a total that could reach well into the tens of billions across multiple stages.
Intel joined the effort in April 2026 and is expected to supply its 14A manufacturing process for the full-scale plant.
Musk has said existing suppliers, including Samsung and TSMC, remain important for near-term needs; Tesla already has production arrangements with Samsung for AI5 and AI6 chips, but that future demand from Optimus robots, Cybercab vehicles, and planned space-based data centers will eventually exceed what the global industry can currently deliver.
Terafab is positioned as the long-term answer to that projected shortfall, and Tesla did something similar during COVID to avoid a chip shortage. This is just a much larger-scale solution.
If the partnership were to materialize, it would add TSMC’s industry-leading strategies to a project that already combines Tesla’s and SpaceX’s capital and offtake with Intel’s process technology. For now, the only public confirmation is Musk’s brief acknowledgement that conversations are occurring.
Tesla’s early strategy for charging units operating within its Robotaxi fleet reveals that the company surely has not lost any of that scrappy DNA that took it from an unlikely success story to the most valuable carmaker in the world.
An observer at a Tesla Supercharger in Austin spotted ten total Robotaxi vehicles arrive: one Cybercab and nine Model Y units. A Tesla employee was waiting at the lot and allowed each unit to park itself; every car that arrived had nobody in it.
Tesla wins FCC approval for wireless Cybercab charging system
The Tesla employee would walk around and plug each car in, adjusting the parking if needed:
So look at what I found. This is how Tesla charges unsupervised robotaxis at a public supercharger. Here is a driverless Cybercab showing up with no one in it. There are 9 other Model Ys that showed up too. A Tesla employee is walking around and plugging each of them in. She also moves the cars if they are not positioned well enough to charge. I love this process. One person charges multiple robotaxis at once
— Abhimanyu Yadav (@WorldlyReviewer) October 3, 2026
It’s a very interesting strategy, but extremely understandable at this early point in the Robotaxi program. It’s only been out for about 15 months, and Cybercab just entered the fleet in early September.
On top of that, Tesla is still working tirelessly on its wireless charging apparatus, and a new patent was just published regarding that product last week.
However, this is just another example of how Tesla still has plenty of that scrappy DNA leftover from the “production hell” days, when CEO Elon Musk slept on the floor of the factory, employees were working crazy hours, Tesla was building Sprung Structures to build cars in, and the company was tiptoeing on the brink of bankruptcy.
@Teslarati Sheer magnitude of the entire production system is hard to appreciate. Almost every element of production is >75% automated. Only wire harnesses & general assembly, which are <10% of production costs, are primarily manual.
— Elon Musk (@elonmusk) October 12, 2020
For now, Tesla is utilizing a simple system for recharging its ride-hailing vehicles, and that is a Tesla employee doing it manually until another solution presents itself. Sure, it’s not the most high-tech thing, and it certainly is not what people might have expected at this point in time, but it works, and it’s keeping the entire suite running.
SpaceX just locked up a NASA record no other U.S. spacecraft can touch
Elon Musk teases TSMC as potential Terafab partner
