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Tesla patents virtualization and machine learning software to improve FSD

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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.

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“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.

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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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Will is an auto enthusiast, a gear head, and an EV enthusiast above all. From racing, to industry data, to the most advanced EV tech on earth, he now covers it at Teslarati.

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Tesla Semi involved in first known fatal crash in Nevada

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Credit: Tesla

A Tesla Semi was involved in a fatal collision on U.S. Highway 50 in Dayton, Nevada, on Sunday, June 28, 2026, marking the first known fatal crash involving the electric Class 8 truck. The incident occurred around 7:20 a.m. at the intersection with Traditions Parkway, approximately 40 miles east of Reno and close to Tesla’s Gigafactory Nevada.

According to the Lyon County Sheriff’s Office and the Nevada State Police Highway Patrol, a semi-truck struck two passenger vehicles stopped at a traffic signal. The truck hit the vehicles from behind. Two people were pronounced dead at the scene, and a third person suffered life-threatening injuries and was flown to a hospital, Forbes reported.

Preliminary statements gathered at the scene by the Lyon County Sheriff’s Office suggested the truck driver may have fallen asleep at the wheel. However, the Nevada Highway Patrol, which is leading the investigation, stated that the official cause has not yet been determined.

Additional information is expected to be released early the following week. The truck was seized for evidence as part of the ongoing probe.

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Responders at the scene included deputies from the Lyon County Sheriff’s Office, personnel from the Nevada Highway Patrol, Central Lyon County Fire Department, and the Nevada Department of Transportation. The crash led to the temporary closure of U.S. 50 in both directions.

The Tesla Semi is Tesla’s battery-electric heavy-duty truck, produced at the nearby Gigafactory in Nevada. Authorities initially described the vehicle as a semi-truck; its make was subsequently confirmed through reporting and scene identification; an interesting bit of information here, as the Semi is not yet available publicly and many do not know that Tesla builds electric trucks.

The investigation remains active, with no further official details on contributing factors or vehicle systems released as of early July 2026.

This incident highlights ongoing scrutiny of commercial vehicle safety on Nevada highways, particularly involving fatigue. Law enforcement continues to gather evidence and witness statements.

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Tesla expands Robotaxi to Florida, marking its third state for autonomy

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Credit: Tesla

Tesla has expanded its Robotaxi program to Miami, Florida, marking the third state the autonomous ride-hailing platform has made its way to since launching last Summer.

Tesla announced today that the Robotaxi suite would now officially launch rides in a geofence in Miami:

The first geofence in Miami covers approximately 10 to 14 square miles. The area appears to be focused on western and central Miami, including Miami International Airport (MIA). It also includes popular routes like SR 826 (Palmetto Expressway), US 41 (Tamiami Trail), and connectors such as SR 968, 953, 959, and 972.

This is Tesla’s initial Miami launch zone, smaller and more targeted than some competitors’ areas (for example, Waymo’s initial rollout was broader in eastern neighborhoods). It prioritizes high-traffic, airport-linked routes before wider expansion.

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The expansion is a huge signal for Tesla that it is now operating in Florida, a heavy-traffic state with many tourist areas, including Fort Lauderdale, Palm Beach, and the Boynton area, all of which are coastal and will attract perhaps millions of tourists in any given year.

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The Tesla Robotaxi network launched last year on June 22, in Austin, Texas, beginning limited commercial operations in that city. It expanded shortly thereafter into the San Francisco Bay Area of California in late July 2025, marking entry into a second state with service covering key areas such as San Francisco, San Jose, and Berkeley.

Full commercial service was achieved in Austin by November 18, 2025, strengthening its presence within Texas before further growth.

In 2026, the network continued expanding across Texas with the addition of Dallas and Houston on April 18, significantly broadening its footprint in the state. This new launch into Miami marks Tesla entering a new state and bringing active locations to include Austin, Dallas, Houston, San Antonio in Texas, and the Bay Area in California.

These sequential expansions have steadily increased the network’s reach across major metropolitan areas in Texas, California, and Florida, focusing on scaling operations city by city and state by state since the initial Austin debut.

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Elon Musk outlines Tesla Optimus production expectations

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Credit: Grok Imagine

Tesla CEO Elon Musk has tempered expectations for the company’s humanoid robot Optimus, emphasizing that initial production will ramp up slowly despite recent progress on the manufacturing line. In a July 1 reply on X, Musk responded to optimistic community speculation by stating, “No, Optimus production will be extremely slow at first, as everything is new. This is not like making a car.”

The comment came in response to a post theorizing that Tesla had accelerated Optimus V3 development and might soon unveil an impressive demonstration with multiple units already in meaningful production. Musk’s clarification highlights the fundamental differences between scaling a novel humanoid robot and Tesla’s established automotive operations, which benefit from over a century of refined supply chains, tooling, and processes.

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Recent updates show tangible advancement. Musk shared a photo of himself walking the Optimus production line at Fremont, where Tesla is converting former Model S/X manufacturing space. According to Q1 2026 earnings commentary, limited production is slated to begin in late July or August 2026 on this converted line.

Tesla Optimus project fires up as Musk sees production line progress

Musk previously noted that Optimus features roughly 10,000 unique parts, making early output rates “literally impossible to predict” and describing them as “quite slow.” A larger dedicated factory at Giga Texas is under construction, targeting higher-volume production around summer 2027 with long-term annual capacity potentially reaching millions of units.

Some experts point out that pioneering humanoid robotics demands inventing new automation techniques, actuator supply chains, and quality-control standards in real time. Unlike vehicles, where components and assembly methods are mature, every element of Optimus—from dexterous hands to AI-integrated movement—requires fresh engineering solutions. Early units are expected to handle simple factory tasks before expanding to more complex roles.

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This cautious approach aligns with Tesla’s history of under-promising and over-delivering on complex technologies. While enthusiasts hoped for rapid deployment, Musk’s message underscores a deliberate strategy: prioritize reliability and iterative improvement over rushed volume.

Analysts suggest the S-curve ramp typical of new manufacturing will eventually accelerate once foundational issues are resolved, positioning Optimus as a potential trillion-dollar product line.

Musk has long envisioned Optimus transforming labor markets, assisting in homes, factories, and hazardous environments. By setting realistic timelines, Tesla aims to build sustainable momentum rather than risk disappointment. As the Fremont line comes online this summer, investors and fans will watch closely for the first production metrics and capability demonstrations.

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