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.
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!
Elon Musk
SpaceX announces new Starship 13 test flight target date
SpaceX has announced a new target date for the thirteenth test flight of Starship: Monday, July 20, with the launch window opening at 6:45 p.m ET/5:45 p.m. CT.
This is the first rescheduling attempt of Starship’s 13th test flight. It was set to launch last night, but SpaceX scrubbed the launch attempt.
🚨 SpaceX is now looking at Monday, July 20th at 6:45 p.m ET/5:45 p.m. CT for the 13th test flight of Starship pic.twitter.com/7s8aMJV5Ge
— TESLARATI (@Teslarati) July 17, 2026
CEO Elon Musk revealed that some of the engines on Starship did not start, which automatically triggers a launch abort. Two of the Raptor engines will be removed and replaced.
To be confident of a good flight, 2 Raptors will be removed & replaced. Most probable launch timing is early next week.
— Elon Musk (@elonmusk) July 17, 2026
SpaceX officially announced the new launch window this morning.
Starship’s 13th test launch comes with a few new objectives, but SpaceX does not plan to attempt a catch of the booster, which it has done several times in the past.
For Starship’s Upper Stage, there are some adjustments to ensure engine reusability that will be assessed during the ascent, and 20 operational Starlink V3 satellites are also set to make their way into space. SpaceX also plans to attempt an in-space relight of a single Raptor engine, which is a critical demonstration for future orbital deorbit, refueling, and deep space maneuvers.
Ultimately, it will splash down in the Indian Ocean.
The continuous tests help SpaceX advance the Starship program toward eventual full reusability, operational Starlink V3 deployment, and future missions, which include NASA’s Artemis program.
Elon Musk
SpaceX Starship Flight 13 aborted at Zero and Musk just told us what broke
Four Raptor engines failed to ignite at T-zero, forcing SpaceX to scrub Starship Flight 13 Thursday.
SpaceX scrubbed the Starship Flight 13 launch attempt Thursday evening at the last possible moment, after four of the Super Heavy booster’s 33 Raptor 3 engines failed to ignite during the startup sequence. The 90-minute window had opened at 6:45 p.m. EDT from Starbase in Boca Chica, Texas, and the countdown had proceeded without issue all day, with more than 11.5 million pounds of liquid methane and liquid oxygen being fully loaded into the rocket before the automated abort triggered. SpaceX’s launch directors posted on X, “Standing down from today’s flight test attempt,” and shut down the livestream shortly after.
Musk confirmed the root cause within hours. “Some of the engines didn’t start, triggering an automatic launch abort,” he wrote on X. “To be confident of a good flight, 2 Raptors will be removed and replaced. Most probable launch timing is early next week.” SpaceX engineers began draining propellant tanks immediately and Booster 20 was rolled back to its hangar for inspection.
The timing adds a layer of significance that did not exist during any of the previous 12 Starship flights. This is the first time SpaceX has attempted to launch Starship since the company made its stock market debut in June, listing under ticker SPCX at $135 per share. Public investors are now watching every Starship outcome in real time, and a last-second abort carries more visibility than it would have six months ago.
Flight 13 was designed to be one of the most consequential tests in the program’s history. It was set to carry 20 Starlink V3 satellites, the first operational payload Starship has ever attempted to deploy. Six of those satellites carried external cameras to photograph Starship’s heat shield from the outside during flight, which would act as a self-inspection approach SpaceX has never attempted before. The mission also needed to complete a Raptor engine relight in space, a step SpaceX skipped on Flight 12 in May after losing an engine during ascent. That Flight 12 booster also flipped 90 degrees off course during its boostback burn when five engines failed to reignite.
SpaceX has not announced an official next launch date. Musk’s “early next week” window points to July 21 or 22 at the earliest, pending the engine swap and a return to the pad.
News
Elon Musk secretly acquires $1B energy company to power the AI future
Elon Musk flew under the radar with his recent purchase of a $1 billion energy company, according to Federal Trade Commission (FTC) documents.
Transaction number 202612350 listed Tesla and SpaceX frontman Elon Musk as the acquiring party and CF APR Super Holdings LLC as the seller, with New APR Energy, LLC as the acquired entity. The deal, which closed without public announcement, came to light on May 14.
BREAKING: Elon Musk acquires Jacksonville power company APR Energy in a deal valued at more than $1,000,000,000.00.
— Polymarket Money (@PolymarketMoney) July 15, 2026
Analysts inferred the deal’s scale from minority stakeholder disclosures, including one report of a 5 percent interest sold for approximately $50.4 million. Fortress Investment Group had purchased APR’s assets in late 2024, rebranded the operation as New APR Energy, and subsequently transferred ownership to Musk.
APR Energy specializes in rapidly deployable power infrastructure. The company maintains one of the world’s largest fleets of mobile gas and diesel turbines, with more than 1.1 gigawatts of generation capacity. Its modular units, which are often trailer-mounted, enable turnkey installations ranging from 20 MW to over 500 MW.
APR provides full engineering, procurement, construction, operation, and maintenance services for behind-the-meter power plants, serving everything from data centers, utilities, and industrial clients.
The firm has expanded aggressively to meet surging demand, recently adding turbines and deploying over 100 MW for a major AI hyperscaler. Its solutions bridge critical gaps where grid interconnections face delays of two to five years, according to Yahoo.
The acquisition means something more for Musk. As he continues to expand projects in artificial intelligence, especially xAI, his AI venture, there is a greater need to supply energy-intensive supercomputing clusters, including the Colossus project, with what they need: reliable and high-capacity power.
Ownership of APR provides immediate access to flexible generation assets that can be deployed adjacent to data centers, reducing dependence on a strained infrastructure. It also complements Tesla’s energy storage business, so Musk will be able to pull from his own entities to address the rapid scaling demands of AI training and compute.