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Tesla 3D labeling is the next big leap for Autopilot
Tesla’s 3D labeling efforts are integral to the development of its Full Self-Driving suite. Using over 2.2 billion miles of real-world driving data from its electric vehicle fleet, the electric car maker has a treasure trove of information about how human drivers behave.
Elon Musk recently confirmed that Tesla is finishing work on Autopilot core foundation code and 3D labeling, and once these are done, users can expect the electric carmaker to roll out more functionalities in a potentially more efficient manner. More advanced features such as Reverse Summon will also be rolled out.
Tesla 3D Labeling: The Next Big Thing
The Tesla CEO has tagged 3D labeling as the next big thing for the company’s efforts to achieve full self-driving. “In terms of labeling, labeling with video in all eight cameras simultaneously. This is a really, I mean in terms of labeling efficiency, arguably like a three order of magnitude improvement in labeling efficiency where Tesla vehicles use all of its eight cameras simultaneously, and that the company has improved significantly in terms of labeling efficiency,” Musk said during the Q4 2019 earnings call.
During Autonomy Day last year, Tesla’s AI head Andrej Karpathy gave the electric vehicle community an idea of how labeling is done. He said annotating data is a very expensive process that initially involved people processing data, but Tesla has also been using information from its fleet to automate the process of labeling using different mechanisms.
For example, in predicting cut-ins, Tesla taps into its fleet for data on such incidents. This information is then automatically annotated and used to train the neural network, which in turn learns from recognizable patterns. This information is then spun until the neural network is trained enough. Improvements in the neural network can then be rolled out as an update for Autopilot.
The same is true according to Karpathy when it comes to object detection. Tesla sources data from its fleet to learn more about different objects and anomalies on the road. With automated 3D labeling, the neural network can more efficiently process the information and learn even about the rarest things one can encounter on the road.
Karpathy and Musk explained how annotations from its fleet help with path prediction. Using trajectories collected from the real-world, the neural network can improve its driving behavior, say while approaching a corner that it doesn’t actively see. This smarter neural network is perfectly demonstrated by an older Model X with early-gen Autopilot negotiating a muddy rural backroad recently, after a storm in the United Kingdom.
All of these things form part of the equation to achieve Full Self-Driving capabilities. Likely through 3D labeling improvements in the past year or so, Tesla has immensely improved driving visualizations in vehicles equipped with Hardware 3, which now identify traffic lights, garbage cans, and detailed road markings, among others. Thus, Elon Musk’s explanation about rewriting the Autopilot foundational code and 3D labeling could be a way of emphasizing that Tesla owners’ investment in the company’s Full Self-Driving suite would be proven worth it and more soon.
Tesla’s FSD computer and autonomy software will transform how humans travel. The company’s vehicles will be smart enough to drive like humans and eventually make the roads a few times safer for everyone. This may also pave the way for Robotaxis and help achieve Musk’s vision of Teslas earning for their owners while they are busy with work or even while relaxing at home. Tesla Robotaxis would be an attractive form of transportation as they will be more cost-efficient compared to driving personal cars, as predicted by ARK Invest.
Autonomy As Key To Profitability
Autonomy will spell profits for Tesla, as Elon Musk explained during the company’s Q4 2019 earnings call. In order to achieve sustained profitability, Tesla needs to produce high volume units with high margins. Musk appears to consider autonomy as key to Tesla’s high margins as well.
“As we’re close to Full Self-Driving, that is just going to become more and more compelling. So that’s for our financial standpoint, that’s the real mind-blowing situation is high-volume, high-margin because of autonomy,” Musk said.
With FSD capabilities, Tesla adds more value proposition that can help sway even more customers to purchase its electric vehicles from the Model 3, Model Y, Model S, Model X, or the Cybertruck. Depending on regulations in specific regions, Tesla can tap into most of its earnings potential, which bodes well since the company has current plans to expand its presence worldwide with Gigafactories in multiple regions.
Tesla’s path to autonomy is only one of the aspects that make it the leader in the electric vehicle industry. Add to that its advancements on car connectivity and battery technology and one will complete the equation why legacy carmakers with the deepest of pockets can only watch in amazement as a relatively young electric car maker dominates the emerging EV industry.
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Tesla FSD fleet is nearing 7 billion total miles, including 2.5 billion city miles
As can be seen on Tesla’s official FSD webpage, vehicles equipped with the system have now navigated over 6.99 billion miles.
Tesla’s Full Self-Driving (Supervised) fleet is closing in on almost 7 billion total miles driven, as per data posted by the company on its official FSD webpage.
These figures hint at the massive scale of data fueling Tesla’s rapid FSD improvements, which have been quite notable as of late.
FSD mileage milestones
As can be seen on Tesla’s official FSD webpage, vehicles equipped with the system have now navigated over 6.99 billion miles. Tesla owner and avid FSD tester Whole Mars Catalog also shared a screenshot indicating that from the nearly 7 billion miles traveled by the FSD fleet, more than 2.5 billion miles were driven inside cities.
City miles are particularly valuable for complex urban scenarios like unprotected turns, pedestrian interactions, and traffic lights. This is also the difference-maker for FSD, as only complex solutions, such as Waymo’s self-driving taxis, operate similarly on inner-city streets. And even then, incidents such as the San Francisco blackouts have proven challenging for sensor-rich vehicles like Waymos.
Tesla’s data edge
Tesla has a number of advantages in the autonomous vehicle sector, one of which is the size of its fleet and the number of vehicles training FSD on real-world roads. Tesla’s nearly 7 billion FSD miles then allow the company to roll out updates that make its vehicles behave like they are being driven by experienced drivers, even if they are operating on their own.
So notable are Tesla’s improvements to FSD that NVIDIA Director of Robotics Jim Fan, after experiencing FSD v14, noted that the system is the first AI that passes what he described as a “Physical Turing Test.”
“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,” Fan wrote in a post on X.
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Tesla starts showing how FSD will change lives in Europe
Local officials tested the system on narrow country roads and were impressed by FSD’s smooth, human-like driving, with some calling the service a game-changer for everyday life in areas that are far from urban centers.
Tesla has launched Europe’s first public shuttle service using Full Self-Driving (Supervised) in the rural Eifelkreis Bitburg-Prüm region of Germany, demonstrating how the technology can restore independence and mobility for people who struggle with limited transport options.
Local officials tested the system on narrow country roads and were impressed by FSD’s smooth, human-like driving, with some calling the service a game-changer for everyday life in areas that are far from urban centers.
Officials see real impact on rural residents
Arzfeld Mayor Johannes Kuhl and District Administrator Andreas Kruppert personally tested the Tesla shuttle service. This allowed them to see just how well FSD navigated winding lanes and rural roads confidently. Kruppert said, “Autonomous driving sounds like science fiction to many, but we simply see here that it works totally well in rural regions too.” Kuhl, for his part, also noted that FSD “feels like a very experienced driver.”
The pilot complements the area’s “Citizen Bus” program, which provides on-demand rides for elderly residents who can no longer drive themselves. Tesla Europe shared a video of a demonstration of the service, highlighting how FSD gives people their freedom back, even in places where public transport is not as prevalent.
What the Ministry for Economic Affairs and Transport says
Rhineland-Palatinate’s Minister Daniela Schmitt supported the project, praising the collaboration that made this “first of its kind in Europe” possible. As per the ministry, the rural rollout for the service shows FSD’s potential beyond major cities, and it delivers tangible benefits like grocery runs, doctor visits, and social connections for isolated residents.
“Reliable and flexible mobility is especially vital in rural areas. With the launch of a shuttle service using self-driving vehicles (FSD supervised) by Tesla in the Eifelkreis Bitburg-Prüm, an innovative pilot project is now getting underway that complements local community bus services. It is the first project of its kind in Europe.
“The result is a real gain for rural mobility: greater accessibility, more flexibility and tangible benefits for everyday life. A strong signal for innovation, cooperation and future-oriented mobility beyond urban centers,” the ministry wrote in a LinkedIn post.
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Tesla China quietly posts Robotaxi-related job listing
Tesla China is currently seeking a Low Voltage Electrical Engineer to work on circuit board design for the company’s autonomous vehicles.
Tesla has posted a new job listing in Shanghai explicitly tied to its Robotaxi program, fueling speculation that the company is preparing to launch its dedicated autonomous ride-hailing service in China.
As noted in the listing, Tesla China is currently seeking a Low Voltage Electrical Engineer to work on circuit board design for the company’s autonomous vehicles.
Robotaxi-specific role
The listing, which was shared on social media platform X by industry watcher @tslaming, suggested that Tesla China is looking to fill the role urgently. The job listing itself specifically mentions that the person hired for the role will be working on the Low Voltage Hardware team, which would design the circuit boards that would serve as the nervous system of the Robotaxi.
Key tasks for the role, as indicated in the job listing, include collaboration with PCB layout, firmware, mechanical, program management, and validation teams, among other responsibilities. The role is based in Shanghai.
China Robotaxi launch
China represents a massive potential market for robotaxis, with its dense urban centers and supportive policies in select cities. Tesla has limited permission to roll out FSD in the country, though despite this, its vehicles have been hailed as among the best in the market when it comes to autonomous features. So far, at least, it appears that China supports Tesla’s FSD and Robotaxi rollout.
This was hinted at in November, when Tesla brought the Cybercab to the 8th China International Import Expo (CIIE) in Shanghai, marking the first time that the autonomous two-seater was brought to the Asia-Pacific region. The vehicle, despite not having a release date in China, received a significant amount of interest among the event’s attendees.
Tesla FSD fleet is nearing 7 billion total miles, including 2.5 billion city miles
Tesla starts showing how FSD will change lives in Europe
