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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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Starlink passes 9 million active customers just weeks after hitting 8 million

The milestone highlights the accelerating growth of Starlink, which has now been adding over 20,000 new users per day.

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Credit: Starlink/X

SpaceX’s Starlink satellite internet service has continued its rapid global expansion, surpassing 9 million active customers just weeks after crossing the 8 million mark. 

The milestone highlights the accelerating growth of Starlink, which has now been adding over 20,000 new users per day.

9 million customers

In a post on X, SpaceX stated that Starlink now serves over 9 million active users across 155 countries, territories, and markets. The company reached 8 million customers in early November, meaning it added roughly 1 million subscribers in under seven weeks, or about 21,275 new users on average per day. 

“Starlink is connecting more than 9M active customers with high-speed internet across 155 countries, territories, and many other markets,” Starlink wrote in a post on its official X account. SpaceX President Gwynne Shotwell also celebrated the milestone on X. “A huge thank you to all of our customers and congrats to the Starlink team for such an incredible product,” she wrote. 

That growth rate reflects both rising demand for broadband in underserved regions and Starlink’s expanding satellite constellation, which now includes more than 9,000 low-Earth-orbit satellites designed to deliver high-speed, low-latency internet worldwide.

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Starlink’s momentum

Starlink’s momentum has been building up. SpaceX reported 4.6 million Starlink customers in December 2024, followed by 7 million by August 2025, and 8 million customers in November. Independent data also suggests Starlink usage is rising sharply, with Cloudflare reporting that global web traffic from Starlink users more than doubled in 2025, as noted in an Insider report.

Starlink’s momentum is increasingly tied to SpaceX’s broader financial outlook. Elon Musk has said the satellite network is “by far” the company’s largest revenue driver, and reports suggest SpaceX may be positioning itself for an initial public offering as soon as next year, with valuations estimated as high as $1.5 trillion. Musk has also suggested in the past that Starlink could have its own IPO in the future. 

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NVIDIA Director of Robotics: Tesla FSD v14 is the first AI to pass the “Physical Turing Test”

After testing FSD v14, Fan stated that his experience with FSD felt magical at first, but it soon started to feel like a routine.

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Credit: Grok Imagine

NVIDIA Director of Robotics Jim Fan has praised Tesla’s Full Self-Driving (Supervised) v14 as the first AI to pass what he described as a “Physical Turing Test.”

After testing FSD v14, Fan stated that his experience with FSD felt magical at first, but it soon started to feel like a routine. And just like smartphones today, removing it now would “actively hurt.”

Jim Fan’s hands-on FSD v14 impressions

Fan, a leading researcher in embodied AI who is currently solving Physical AI at NVIDIA and spearheading the company’s Project GR00T initiative, noted that he actually was late to the Tesla game. He was, however, one of the first to try out FSD v14

“I was very late to own a Tesla but among the earliest to try out FSD v14. It’s perhaps the first time I experience an AI that passes the Physical Turing Test: after a long day at work, you press a button, lay back, and couldn’t tell if a neural net or a human drove you home,” Fan wrote in a post on X. 

Fan added: “Despite knowing exactly how robot learning works, I still find it magical watching the steering wheel turn by itself. First it feels surreal, next it becomes routine. Then, like the smartphone, taking it away actively hurts. This is how humanity gets rewired and glued to god-like technologies.”

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The Physical Turing Test

The original Turing Test was conceived by Alan Turing in 1950, and it was aimed at determining if a machine could exhibit behavior that is equivalent to or indistinguishable from a human. By focusing on text-based conversations, the original Turing Test set a high bar for natural language processing and machine learning. 

This test has been passed by today’s large language models. However, the capability to converse in a humanlike manner is a completely different challenge from performing real-world problem-solving or physical interactions. Thus, Fan introduced the Physical Turing Test, which challenges AI systems to demonstrate intelligence through physical actions.

Based on Fan’s comments, Tesla has demonstrated these intelligent physical actions with FSD v14. Elon Musk agreed with the NVIDIA executive, stating in a post on X that with FSD v14, “you can sense the sentience maturing.” Musk also praised Tesla AI, calling it the best “real-world AI” today.

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Tesla AI team burns the Christmas midnight oil by releasing FSD v14.2.2.1

The update was released just a day after FSD v14.2.2 started rolling out to customers. 

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Credit: Grok

Tesla is burning the midnight oil this Christmas, with the Tesla AI team quietly rolling out Full Self-Driving (Supervised) v14.2.2.1 just a day after FSD v14.2.2 started rolling out to customers. 

Tesla owner shares insights on FSD v14.2.2.1

Longtime Tesla owner and FSD tester @BLKMDL3 shared some insights following several drives with FSD v14.2.2.1 in rainy Los Angeles conditions with standing water and faded lane lines. He reported zero steering hesitation or stutter, confident lane changes, and maneuvers executed with precision that evoked the performance of Tesla’s driverless Robotaxis in Austin.

Parking performance impressed, with most spots nailed perfectly, including tight, sharp turns, in single attempts without shaky steering. One minor offset happened only due to another vehicle that was parked over the line, which FSD accommodated by a few extra inches. In rain that typically erases road markings, FSD visualized lanes and turn lines better than humans, positioning itself flawlessly when entering new streets as well.

“Took it up a dark, wet, and twisty canyon road up and down the hill tonight and it went very well as to be expected. Stayed centered in the lane, kept speed well and gives a confidence inspiring steering feel where it handles these curvy roads better than the majority of human drivers,” the Tesla owner wrote in a post on X.

Tesla’s FSD v14.2.2 update

Just a day before FSD v14.2.2.1’s release, Tesla rolled out FSD v14.2.2, which was focused on smoother real-world performance, better obstacle awareness, and precise end-of-trip routing. According to the update’s release notes, FSD v14.2.2 upgrades the vision encoder neural network with higher resolution features, enhancing detection of emergency vehicles, road obstacles, and human gestures.

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New Arrival Options also allowed users to select preferred drop-off styles, such as Parking Lot, Street, Driveway, Parking Garage, or Curbside, with the navigation pin automatically adjusting to the ideal spot. Other refinements include pulling over for emergency vehicles, real-time vision-based detours for blocked roads, improved gate and debris handling, and Speed Profiles for customized driving styles.

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