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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?
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.”
Maximum smoothness https://t.co/p4aM3StgRk
— Tesla (@Tesla) March 15, 2025
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.
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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.
Tesla FSD testers in China do seem to be built different. That’s some REALLY rural roads!
— TESLARATI (@Teslarati) March 14, 2025
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.
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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.
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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In a new note to investors on Tuesday, Morgan Stanley analyst Andrew Percoco said that Tesla has one big financial question to answer for investors regarding its Robotaxi rollout, Full Self-Driving software, and Optimus.
Percoco said in the note that, for the most part, investors are still very positive about the direction the company is headed. However, there are some things the firm would like to see, and they have to do with financials.
Tesla (TSLA) Q2 2026 earnings results: miss on EPS, beat on revenue
Tesla bulls are more than convinced that the company’s Full Self-Driving software is proof it can develop physical AI. Financially, however, there are still some questions, especially on elevated spending, which CEO Elon Musk said would occur as the company works to roll out Robotaxi faster and continue developing its Optimus robot.
The latter two are where Tesla will have to prove progress to investors, as Percoco writes that both projects “will require clearer evidence that Robotaxi is scaling and more tangible Optimus proof points to support the ROI on elevated capex.”
Percoco said the second quarter earnings call did not change his long-term thesis of where Tesla is positioned in the AI race, which is out in front. However, there are concerns that weaker gross margins and higher R&D spend will stress financials, and that has “sharpened our (and investors’) focus on measurable progress across Robotaxi and Optimus.”
Additionally, Robotaxi still needs to be proven with more operation in existing cities while maintaining safety but improving how many rides it gives in any given time, he said. For Optimus, Percoco wrote that he is “still looking for evidence beyond commentary around SOP.”
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Morgan Stanley put Percoco in charge of covering Tesla after long-time analyst Adam Jonas transitioned to the automotive side.
Currently, Morgan Stanley has a $415 price target on Tesla and a ‘Hold’ rating on the stock. It is trading at around $330 at the time of publication, which was 2:30 P.M. on the East Coast.
SpaceX’s massive investment in AI will make it a big winner, Argus Research said after the company’s successful earnings call last week.
The firm also upgraded shares to a Buy from Hold and set a $160 price target.
SpaceX (NASDAQ: SPCX) is currently recovering from its heavy AI infrastructure investments, as it spent nearly $16 billion in Q2 alone. The company did this primarily by monetizing high-demand GPU compute capacity at a much faster pace than traditional data center economics would suggest.
Company CFO Bret Johnsen said that SpaceX would be able to pay back anything on new deployments within a year.
There are plenty of ways the company can do this:
Leasing excess compute capacity through contracts
SpaceX has already built Colossus and Colossus II, largely for its own model training. However, much of that capacity is already rented out to third parties. It already has major deals with Anthropic, Google, and Reflection AI. These partnerships are adding billions per month to SpaceX’s spreadsheet.
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High utilization driven by industry-wide scarcity
The demand for advanced AI training and inference capacity continues to exceed what is available for use. SpaceX can fill new racks quickly after they come online, so the capital deployed converts into revenue with minimal idle time.
Additionally, management and outside observers have described the new compute capital as behaving more like a cost-of-goods-sold than traditional multi-year capex, especially because of this rapid monetization pattern.
Capacity has already scaled from ~0.4 GW a year to 1.4 GW annually by the end of Q2. There are targets of more than 2 GW by year-end.
High incremental margins on the rental business once capacity is online
GPU cloud providers often operate at strong gross margins. SpaceX can monetize capacity that was already partially built or can be added efficiently. This means that incremental EBITDA margins on the rental revenue are usually high. This accelerates cash recovery relative to the gross capital outlay.
Parallel monetization of its own AI software and applications
Beyond pure infrastructure rental, SpaceX also generates revenue from Grok through subscriptions and usage, from X through ads, data, and other related services, enterprise APIs, and the planned integration of the Cursor coding tools acquisition.
These application layers ride on the same compute infrastructure and provide additional high-margin streams that could offset build-out costs. AI-segment revenue overall rose sharply to about $2.6 billion in Q2, according to Motley Fool. This was driven primarily by the infrastructure contracts, but the software side is also partially responsible.
Efficient, large-scale deployment and vertical integration advantages
SpaceX has emphasized the rapid construction of power and cooling infrastructure and favorable cost-per-megawatt economics relative to industry benchmarks in some disclosures.
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Combined with its ability to scale capacity aggressively and the fact that many contracts start generating revenue within months of capacity coming online, the effective payback compresses dramatically compared with more conventional multi-year data-center projects.
SpaceX’s dominant near-term recovery path will turn the AI clusters into a hyperscale-style compute rental business for other leading AI companies while still using a portion for internal models.
Tesla headlights have caused a recall of over 20,000 of the company’s two most popular vehicles, the Model 3 and Model Y, due to the low-beam bulb exceeding the maximum allowed intensity according to federal standards.
Tesla initiated the recall with the National Highway Traffic Safety Administration (NHTSA) this morning, stating that the low-beam output “exceeds the maximum allowed intensity in the outer upper-right and outer upper-left areas of the 10U and 90U zone, as prescribed in FMVSS No. 108.”
Tesla sourced the impacted headlights from Marelli Automotive Lighting, a Mexico-based company. The recall impacts 2020-2023 Model Y vehicles and 2017-2023 Model 3 vehicles. It is estimated that every VIN in this recall is impacted by the defect.
🚨 Tesla is recalling 20,349 2020-23 Model Y vehicles and 2017-23 Model 3 vehicles due to an excessively bright headlamp low beam.
Currently, there is no remedy plan in place, as it is still being developed. pic.twitter.com/y34cIO2U0B
— TESLARATI (@Teslarati) August 11, 2026
Typically, Tesla would remedy recalls of this nature through an Over-the-Air software update, which has been a major focus of criticism by the company and its supporters because the NHTSA still refers to it as a “recall,” even though it requires no action by the vehicle owner. The fix is shipped over the internet and downloaded to the car.
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However, there appears to be a potentially different solution for this problem. Tesla has not developed a remedy for this issue, so it could potentially be on the way. The big issue appears to be the fact that these recalled lamps are out of production, and this is an old body style for both vehicles. The headlights and front-end designs are completely different.
Tesla switched to another supplier when the affected headlight design was discontinued. It plans to begin notifying owners of their remedy options by September 15.
Tesla filed a petition protesting the recall to fix the vehicles’ headlight issue, but the NHTSA denied it. Now, Tesla will come up with a solution to fix it.
Tesla has one big financial question to answer for investors: Morgan Stanley
SpaceX AI investment gamble will make it a big winner, firm says
