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Tesla used this clever workaround to train FSD for China’s roads

Credit: @DriveGreen80167/X

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An initial version of what is effectively Tesla’s Full Self-Driving (FSD) has started going live in China this week, and some early users are commenting on how well it’s performing in the country—despite only being available in North America previously.

In response to some of these reports, Elon Musk has revealed how the system has so quickly adapted to China’s road signs and traffic laws, noting that the company’s emphasis on video-based training makes the FSD-based system able to learn so quickly.

On Tuesday, users on X commented on how the FSD system had seemingly begun learning about driving in China ahead of time, and with “virtually no additional software development costs,” as Ray4Tesla points out. In response to him and James Douma, Musk said that Tesla deployed a pretty straightforward solution for pre-training FSD on China’s roads, utilizing videos like how its systems in North America are trained.

“We just used publicly available video on the Internet of roads and signs in China and used that to train in sim,” Musk says.

READ MORE ON FSD SUPERVISED: Tesla’s FSD rollout in Mexico is a bigger deal than it seems

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Crucially, the process was similar to how Tesla’s camera-based, “vision-only” system works for FSD Supervised in North America, but instead using a simulator in China ahead of the access to real-world video. Now, with the service starting to roll out (despite not being termed FSD just yet due to some data privacy laws in China), Tesla should soon or already be able to start utilizing real-time footage to train the model, building on top of the simulated experiences grabbed from online.

Back in 2023, ahead of the launch of FSD beta v12, Musk and FSD engineers pointed out that the then-forthcoming version would play a key role in solving autonomy—especially due to its move toward a neural network that would be trained on video instead of on a “rules-based approach” and human-written code.

“FSD (Supervised) v12 upgrades the city-streets driving stack to a single end-to-end neural network trained on millions of video clips, replacing over 300k lines of explicit C++ code,” Tesla wrote in the release notes for the version.

Now well into v13 and having dropped the beta moniker nearly a year ago, Tesla has continued to tout its non-Lidar, camera-only based system, with executives regularly highlighting FSD’s scalability. While first reviews in China seem generally positive, we can definitely expect to see how the system fairs in new markets in the coming months, as multiple companies race toward commercial autonomy.

What are your thoughts? Let me know at zach@teslarati.com, find me on X at @zacharyvisconti, or send us tips at tips@teslarati.com.

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Elon Musk discusses Tesla FSD rollout challenges for Europe and China

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Zach is a renewable energy reporter who has been covering electric vehicles since 2020. He grew up in Fremont, California, and he currently lives in Colorado. His work has appeared in the Chicago Tribune, KRON4 San Francisco, FOX31 Denver, InsideEVs, CleanTechnica, and many other publications. When he isn't covering Tesla or other EV companies, you can find him writing and performing music, drinking a good cup of coffee, or hanging out with his cats, Banks and Freddie. Reach out at zach@teslarati.com, find him on X at @zacharyvisconti, or send us tips at tips@teslarati.com.

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Tesla to open source Model S and Model X designs and software

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Credit: Tesla

In a move echoing its earlier commitment to open innovation, Tesla CEO Elon Musk announced recently that the company plans to make the design and software of its Model S and Model X fully open source.

This follows the same approach Tesla took with its original Roadster, releasing all available design, engineering, and diagnostic materials in November 2023 so that “whatever we have, you now have.”

The Model S, introduced in 2012, was Tesla’s first mass-produced vehicle and a groundbreaking luxury electric sedan. It offered impressive range, rapid acceleration, and over-the-air software updates that redefined expectations for electric cars.

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The Model X, launched in 2015, built on that foundation as a high-performance electric SUV notable for its distinctive falcon-wing doors, spacious interior, and advanced safety features. Both models served as flagships that helped establish Tesla as a leader in the EV industry and popularized long-range battery-electric vehicles.

Production of the Model S and Model X was wound down earlier in 2026, with manufacturing ending in the second quarter. Tesla redirected the Fremont factory space previously used for these vehicles toward higher-priority projects, including Optimus humanoid robots and the Cybercab autonomous vehicle.

By the time of Musk’s open-source announcement, custom orders had closed and only remaining inventory was available.

Open-sourcing the designs and software offers several clear advantages. Owners of these aging but still capable vehicles gain better access to technical documentation, diagnostic tools, and software resources, making independent repairs and modifications easier and more affordable.

Independent repair shops and third-party specialists can support the large existing fleet without relying solely on Tesla’s service network. Enthusiasts and engineers can study real-world implementations of Tesla’s battery, powertrain, and software systems, potentially accelerating broader industry progress in electric mobility.

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The step aligns with Tesla’s 2014 patent pledge and its overall mission to advance sustainable transport by sharing hard-won knowledge rather than locking it behind proprietary walls.

By releasing these materials now that the models have left production, Tesla ensures continued support for its early adopters while freeing internal resources for future technologies. The open-source release of the original Roadster already enabled simulations, community projects, and deeper technical understanding.

Extending that practice to the Model S and Model X should deliver similar benefits on a larger scale, helping keep these influential vehicles relevant and repairable for years to come

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Tesla flexes incredible Robotaxi metric that skeptics will hate

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Credit: Tesla

Tesla flexed one incredible Robotaxi metric during the Q2 Earnings Call that skeptics have to hate to hear. The company’s platform has already driven more than 380,000 miles of unsupervised ride-hailing across several states with no notable incidents.

During the company’s Q2 Earnings Call on Wednesday, Vice President of AI, Ashok Elluswamy, said:

“First of all, I’d like to state that the Robotaxi program has been operating extremely well. Especially in terms of safety, the program has had an impeccable safety record. We have driven more than 380,000 miles of unsupervised Robotaxi, now across six cities in two different states. We have had zero notable incidents. Any reports have been of other actors impacting us when we were stationary. I like to emphasize how safe the operation has been so far. Zero notable incidents over 380,000 miles.”

Elluswamy’s claim over Robotaxi miles is a significant milestone for Tesla in the grand scheme, especially considering this is a sizeable number of miles without any incident.

Tesla’s self-driving approach is much different than that of other companies. Tesla has maintained that vision is the only thing needed to have a solid and effective self-driving suite. Many self-driving companies utilize things like LiDAR, sensors, and other elements to improve performance, but Elluswamy sent a jab at those who believe it’s needed.

“Historically, the so-called experts have always claimed that you need LiDARs, radars, HD maps, and the entire kitchen sink to drive safely. Here we show that such is not true. You can have safe, comfortable, and affordable autonomy with just cameras. This record should be a huge validation of Tesla’s entire AI approach.”

The feat of accumulating this many miles without any driver behind the wheel is impressive. The thing is, Tesla is also doing this across several different locations, with varying traffic rules, pedestrian levels, weather patterns, and other important factors.

While Tesla is not ready to roll out an unsupervised platform completely, it is a slow but steady indication that the company is well on its way to figuring things out.

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The company’s attitude toward expansion is slow, safe, and controlled, and despite this huge milestone, it will still be some time until we see Tesla truly unleash unsupervised rides more aggressively.

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SpaceX Starship just nailed something it’s never done before

SpaceX’s Starship flew successfully Friday, landing both stages and deploying its first Starlink V3 satellites.

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Starship’s thirteenth test flight delivered exactly what SpaceX needed with a clean liftoff, two successful stage recoveries, and the first real payload the vehicle has ever carried to space. Booster 20 and Ship 40 lifted off at 5:51 p.m. CT from Starbase, and by the time the mission wrapped roughly an hour later, both halves of the rocket had done exactly what they were supposed to do.

Booster 20 separated from Ship 40 a few minutes into the flight and stuck a controlled splashdown in the Gulf of Mexico about six minutes after liftoff. That is a meaningful turnaround from Flight 12 in May, when the booster lost several engines during its boostback burn before a hard water landing attempt.


Starship 40’s performance was arguably the bigger win. The vehicle deployed the first 20 operational Starlink V3 satellites Starship has ever carried, then flew a suborbital arc to a landing in the Indian Ocean that SpaceX commentator Dan Huot called the company’s softest splashdown yet. “This is a dream scenario for this team that’s trying to get this heat shield data,” Huot said on the live broadcast, according to Space.com’s live coverage. “I’m a little over the moon right now. Wow. Lucky number 13.”

Unlike the mass simulators SpaceX flew on Flight 12, these were production Starlink V3 satellites, meant to extend solar arrays and antennas and attempt to link with the broader constellation before reentering minutes later. Getting real hardware through a full deploy sequence on only the second flight of the V3 generation keeps Starship on schedule for the payload work NASA is counting on for future Artemis lunar landings.

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— TESLARATI (@Teslarati) July 25, 2026

The flight also arrives at a moment when SpaceX needed a win. SPCX has traded below its $135 IPO price since mid-July, as Teslarati reported when the mission slipped to Friday, and short interest has climbed to roughly a third of the tradable float. A clean flight will not fix a balance sheet, but it does answer the one question SpaceX absolutely needed answered this week: whether the fixes made after the July 16 abort would hold up under real flight conditions. They did, on both stages, on the first try after the redesign.

SpaceX has not set a target date for Flight 14, though the company has said it wants to push toward an orbital attempt on the next mission. After Friday, that goal looks a lot more within reach.

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