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Watch Tesla’s FSD tackle water cup challenge, dirt roads in China

How does Tesla’s Full Self-Driving face off against competitors in China when it comes to smoothness and scalability?

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Credit: 王船船 | Douyin (via Tesla on X)

Tesla’s Full Self-Driving (FSD) started going out for testing in China last month, representing the first market outside of North America to get the software. Amidst competition in the automated driving space from a number of other Chinese companies, Tesla’s FSD seems to be impressing in early reviews, with recent reviews highlighting both the software’s smoothness and its ability to adapt and perform well on non-traditional roads.

In a Saturday video originally posted by user 王船船 on Douyin, the Chinese version of TikTok, a driver utilizes the Supervised FSD system while performing what’s called the “water challenge,” in which a cup of water is balanced on the driver’s side window ledge to see if driving is smooth enough to avoid spilling.

The drive spans a little more than four minutes, and the system manages to make it through without the water spilling in any substantial quantities. The driver mostly remains on city streets, but you can see a handful of quick, unexpected stops, turns, and other maneuvers that one might expect to make the cup tip completely.

The video was also reposted on X by Tesla’s main account, with the company highlighting the system’s “maximum smoothness” as demonstrated in the video. Tesla VP of AI Ashok Elluswamy also reposted the video, saying in a separate follow-up post that “FSD’s been prepared for this one.”

Although Tesla’s FSD system didn’t have access to real-world driving data from the company’s vehicles at the time of its launch in China, Elon Musk recently explained that the company used publicly available video from the internet to help pre-train FSD for Chinese streets and traffic laws.

In addition to helping with city streets, Tesla has explained in the past that its camera- and video-based FSD neural network training makes the system easily scalable to multiple countries, fringe traffic cases, and even less traditional roads.

As another example of this in China, FSD testers also took to some dirt roads last week, showing just how well the software seems to handle some seemingly-deep and super-narrow back roads. You can see excerpts from this video below, or check out the full 25-minute version from user AE68 on Douyin.

READ MORE ON TESLA CHINA: Cheaper Tesla Model Y may launch in China

Tesla’s FSD in China amidst local competition

Tesla officially launched a localized data privacy version of FSD Supervised in China last month, The launch came amidst a headstart from multiple competitors in the autonomous driving space, including from Chinese automakers Baidu, Huawei, and still others.

The Avatr 11 electric vehicle (EV), a jointly created project from Changan New Energy, CATL, and Huawei, was recently seen being tested by Out of Spec’s Kyle Conner. The system uses Huawei’s latest automated driving system technology, Qiankun ADS 3.2, which Conner recently said was “the best driver assistance he’s ever experienced” in a recent review on his trip to China.

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You can see this video and an additional video from Conner and Out of Spec discussing the emerging autonomous vehicle industry in China below. It’s also worth noting that both of these were released just a few weeks before Tesla’s first version of FSD launched in the country.

The Best FSD System In China! 1 Hour Drive Using Huawei Qiankun ADS 3.2 Installed In Avatr 11 (2/1/25)

The EV Industry Isn’t Ready For China’s FSD Breakthrough (2/2/25)

Elon Musk clarifies the holdup with Tesla Full Self-Driving launch in Europe

 

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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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Elon Musk

Tesla’s Elon Musk: 10 billion miles needed for safe Unsupervised FSD

As per the CEO, roughly 10 billion miles of training data are required due to reality’s “super long tail of complexity.” 

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Credit: @BLKMDL3/X

Tesla CEO Elon Musk has provided an updated estimate for the training data needed to achieve truly safe unsupervised Full Self-Driving (FSD). 

As per the CEO, roughly 10 billion miles of training data are required due to reality’s “super long tail of complexity.” 

10 billion miles of training data

Musk comment came as a reply to Apple and Rivian alum Paul Beisel, who posted an analysis on X about the gap between tech demonstrations and real-world products. In his post, Beisel highlighted Tesla’s data-driven lead in autonomy, and he also argued that it would not be easy for rivals to become a legitimate competitor to FSD quickly. 

“The notion that someone can ‘catch up’ to this problem primarily through simulation and limited on-road exposure strikes me as deeply naive. This is not a demo problem. It is a scale, data, and iteration problem— and Tesla is already far, far down that road while others are just getting started,” Beisel wrote. 

Musk responded to Beisel’s post, stating that “Roughly 10 billion miles of training data is needed to achieve safe unsupervised self-driving. Reality has a super long tail of complexity.” This is quite interesting considering that in his Master Plan Part Deux, Elon Musk estimated that worldwide regulatory approval for autonomous driving would require around 6 billion miles. 

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FSD’s total training miles

As 2025 came to a close, Tesla community members observed that FSD was already nearing 7 billion miles driven, with over 2.5 billion miles being from inner city roads. The 7-billion-mile mark was passed just a few days later. This suggests that Tesla is likely the company today with the most training data for its autonomous driving program. 

The difficulties of achieving autonomy were referenced by Elon Musk recently, when he commented on Nvidia’s Alpamayo program. As per Musk, “they will find that it’s easy to get to 99% and then super hard to solve the long tail of the distribution.” These sentiments were echoed by Tesla VP for AI software Ashok Elluswamy, who also noted on X that “the long tail is sooo long, that most people can’t grasp it.”

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Tesla earns top honors at MotorTrend’s SDV Innovator Awards

MotorTrend’s SDV Awards were presented during CES 2026 in Las Vegas.

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Credit: Tesla China

Tesla emerged as one of the most recognized automakers at MotorTrend’s 2026 Software-Defined Vehicle (SDV) Innovator Awards.

As could be seen in a press release from the publication, two key Tesla employees were honored for their work on AI, autonomy, and vehicle software. MotorTrend’s SDV Awards were presented during CES 2026 in Las Vegas.

Tesla leaders and engineers recognized

The fourth annual SDV Innovator Awards celebrate pioneers and experts who are pushing the automotive industry deeper into software-driven development. Among the most notable honorees for this year was Ashok Elluswamy, Tesla’s Vice President of AI Software, who received a Pioneer Award for his role in advancing artificial intelligence and autonomy across the company’s vehicle lineup.

Tesla also secured recognition in the Expert category, with Lawson Fulton, a staff Autopilot machine learning engineer, honored for his contributions to Tesla’s driver-assistance and autonomous systems.

Tesla’s software-first strategy

While automakers like General Motors, Ford, and Rivian also received recognition, Tesla’s multiple awards stood out given the company’s outsized role in popularizing software-defined vehicles over the past decade. From frequent OTA updates to its data-driven approach to autonomy, Tesla has consistently treated vehicles as evolving software platforms rather than static products.

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This has made Tesla’s vehicles very unique in their respective sectors, as they are arguably the only cars that objectively get better over time. This is especially true for vehicles that are loaded with the company’s Full Self-Driving system, which are getting progressively more intelligent and autonomous over time. The majority of Tesla’s updates to its vehicles are free as well, which is very much appreciated by customers worldwide.

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Elon Musk

Judge clears path for Elon Musk’s OpenAI lawsuit to go before a jury

The decision maintains Musk’s claims that OpenAI’s shift toward a for-profit structure violated early assurances made to him as a co-founder.

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Gage Skidmore, CC BY-SA 4.0 , via Wikimedia Commons

A U.S. judge has ruled that Elon Musk’s lawsuit accusing OpenAI of abandoning its founding nonprofit mission can proceed to a jury trial. 

The decision maintains Musk’s claims that OpenAI’s shift toward a for-profit structure violated early assurances made to him as a co-founder. These claims are directly opposed by OpenAI.

Judge says disputed facts warrant a trial

At a hearing in Oakland, U.S. District Judge Yvonne Gonzalez Rogers stated that there was “plenty of evidence” suggesting that OpenAI leaders had promised that the organization’s original nonprofit structure would be maintained. She ruled that those disputed facts should be evaluated by a jury at a trial in March rather than decided by the court at this stage, as noted in a Reuters report.

Musk helped co-found OpenAI in 2015 but left the organization in 2018. In his lawsuit, he argued that he contributed roughly $38 million, or about 60% of OpenAI’s early funding, based on assurances that the company would remain a nonprofit dedicated to the public benefit. He is seeking unspecified monetary damages tied to what he describes as “ill-gotten gains.”

OpenAI, however, has repeatedly rejected Musk’s allegations. The company has stated that Musk’s claims were baseless and part of a pattern of harassment.

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Rivalries and Microsoft ties

The case unfolds against the backdrop of intensifying competition in generative artificial intelligence. Musk now runs xAI, whose Grok chatbot competes directly with OpenAI’s flagship ChatGPT. OpenAI has argued that Musk is a frustrated commercial rival who is simply attempting to slow down a market leader.

The lawsuit also names Microsoft as a defendant, citing its multibillion-dollar partnerships with OpenAI. Microsoft has urged the court to dismiss the claims against it, arguing there is no evidence it aided or abetted any alleged misconduct. Lawyers for OpenAI have also pushed for the case to be thrown out, claiming that Musk failed to show sufficient factual basis for claims such as fraud and breach of contract.

Judge Gonzalez Rogers, however, declined to end the case at this stage, noting that a jury would also need to consider whether Musk filed the lawsuit within the applicable statute of limitations. Still, the dispute between Elon Musk and OpenAI is now headed for a high-profile jury trial in the coming months.

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