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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.
Tesla has introduced an enhanced visualization in its Supercharger navigation system, building directly on the Site Maps feature rolled out a few months ago.
This latest software update adds detailed 3D icons that represent specific vehicle models parked at charging stalls, offering drivers a more precise view of site occupancy and layout.
The Site Maps debuted in Tesla’s 2025 Holiday Update, providing 3D overviews of select Supercharger locations with real-time stall availability.
Tesla supplements Holiday Update by sneaking in new Full Self-Driving version
Drivers could see which spots were open, occupied, or out of service when navigating to supported stations.
Now, the system takes this capability further by rendering accurate representations of Tesla vehicles, including distinctions between models such as the Model 3, Model Y, Model S, Model X, and Cybertruck. These icons appear as lifelike 3D renderings, complete with recognizable shapes and proportions that match the actual cars charging at the site:
Supercharger update now shows type of Tesla at charger as well.
Pretty cool. pic.twitter.com/J3NRSIgM0m
— DennisCW | wen my L (@DennisCW_) June 2, 2026
This refinement improves the user experience during road trips and daily charging stops. As drivers approach a Supercharger, the navigation display now shows not just generic occupied markers but identifiable vehicle types plugged into each stall.
Blue indicators highlight active charging sessions, while other visual cues denote availability or maintenance status. The feature integrates seamlessly with the existing map interface, allowing quick assessment of the best available spot based on vehicle size and positioning.
Tesla continues to expand the availability of these detailed Site Maps across its global network. Initially piloted at a limited number of locations, the rollout has progressed steadily, with more stations gaining support in recent software versions.
Owners benefit from better planning, as the system helps identify compatible stalls and reduces uncertainty upon arrival. The update reflects Tesla’s ongoing commitment to refining its navigation and charging ecosystem through iterative software improvements.
In addition to model-specific icons, the enhanced maps maintain all prior functionalities, such as integration with nearby amenities and energy usage predictions. This ensures a comprehensive tool for efficient Supercharging.
As Tesla’s fleet grows and the network scales, such features play a key role in optimizing the overall ownership experience. Future updates may extend similar visualizations to additional sites and incorporate even more data points for drivers.
With this piggyback enhancement, Tesla demonstrates how small but thoughtful additions can elevate an already useful tool, making Supercharger visits smoother and more informed for its customers. The company is expected to broaden the feature’s reach in upcoming releases, further solidifying its leadership in EV charging infrastructure.
Tesla Full Self-Driving v14.3.3 driver monitoring was reportedly scaled back in recent releases, but a new version that was released in the early hours of June 3 aimed to do a better job of keeping those in control of their cars honest, according to release notes.
The release notes for FSD v14.3.3, via Software Version 2026.14.6.7 added:
“Improved driver monitoring system sensitivity with better eye gaze tracking, eye wear handling, and higher accuracy in variable lighting conditions.”
However, Tesla said this was already enabled in the first rollout of FSD v14.3.3 in late May. We tested it anyway, especially as the Standard Speed Profile seemed less-than-worried about what you were doing during operation.
I decided to try out the Hurry and Mad Max Speed Profiles for this test, and it gave me results that I would have expected. Tesla has evidently ramped up driver monitoring based on the Speed Profile you are using to travel.
The more aggressive the Speed Profile, the more on the hook you will be for taking your attention away from the road. Our testing showed that Mad Max was less likely to allow you to do normal things like change music or adjust navigation without getting an on-screen warning or nag from the driver monitoring system.
Hurry Mode Results
On Hurry, the driver monitoring system on FSD v14.3.3, via Software Version 2026.14.6.7, was more restrictive than Standard but less restrictive than Mad Max. I found that I could scroll through music options for a considerable amount of time, more than 30 seconds:
Roughly :31 between first touching the center screen and getting the first nag
— TESLARATI (@Teslarati) June 3, 2026
Standard gave me about 80 seconds of phone scrolling with absolutely no nags or warnings in a previous test. It is worth noting that this was a previous branch of v14.3.3, but Standard is such a goodie-two-shoes on the road that it is my impression it would not change much.
Here’s an 80-second phone nag test on Tesla FSD v14.3.3.
No alerts, no nagging, no annoyance. https://t.co/1dxvTOw5Cn pic.twitter.com/vYViFpjfoK
— TESLARATI (@Teslarati) May 29, 2026
Mad Max Results
I spent the majority of the drive on Mad Max to see how it truly reacted to the driver having their attention elsewhere. While I did do a short phone test, I am aiming to steer away from those and use the center screen. I think it is a valid criticism that the phone test is dangerous and, not to mention, illegal in Pennsylvania. Changing the navigation and music is a more reasonable, more responsible, and safer test.
With Mad Max being the fastest and most aggressive Speed Profile, I anticipated this being the quickest mode to give me an alert that I needed to look at the road. That was the case with music:
🎥 Testing Tesla FSD v14.3.3 (via 2026.14.6.7) nags on Mad Max https://t.co/qZALU2OujY pic.twitter.com/XddOJ0D47x
— TESLARATI (@Teslarati) June 3, 2026
As well as adjusting Navigation, when I received two nags:
🎥 Testing Tesla FSD v14.3.3 (via 2026.14.6.7) nag while adjusting navigation
Two nags here https://t.co/qZALU2OujY pic.twitter.com/xa3dtaDG1L
— TESLARATI (@Teslarati) June 3, 2026
These nags were more than reasonable, and I think it’s probably good that Tesla is ramping up the driver monitoring. I do believe that it should be relatively strict across all of the Speed Profiles, especially with phone use. When using the center screen, the nag intervals should be based on the speed profile you are utilizing at the time.
These driver monitoring adjustments are a great thing to have while FSD is still under its “Supervised” moniker, but I expect Tesla to continue pushing the limits on what it will allow, especially considering CEO Elon Musk has hinted that phone use is capable with the more recent versions.
You can watch the full drive on YouTube below:
Tesla has responded to the skeptics of its Robotaxi program by launching a massive expansion of the unsupervised program in its initial rollout city of Austin.
The company’s geofence, the enabled area of operation for rides, now covers the entire Austin Metropolitan area, an incredible move just days after media headlines attempted to discredit the ride-hailing service.
Those who have access to the Tesla Robotaxi app on their smartphones can now request a ride in any portion of the Austin Metro area. The company confirmed this on the social media platform X:
Unsupervised Robotaxi now in the entire Austin Metro area https://t.co/eXNBdarvVS
— Tesla Robotaxi (@robotaxi) June 3, 2026
This is Tesla’s fifth expansion of the geofence, with the others occurring in July, early August, late August, and late October 2025. It has remained at that size since October 26, but Tesla has now more than doubled that size.
It is now covering the entire area, including suburbs like Pflugerville and Manor, as well as I-35 highways, Gigafactory Texas, and the Austin-Bergstrom Airport.
The move comes just days after various media outlets highlighted the small fleet size of Tesla’s Robotaxi fleet in Austin, something that is a reasonable criticism but an understandable move on the company’s part to prioritize safety.
Tesla has expanded its Robotaxi geofence many times, but its fleet has remained at a relatively conservative size as the company continues to push safety as its most crucial metric.
The latest expansion is a key indicator of Tesla’s comfort level to expand the ride-hailing service. The move shows Tesla is scaling unsupervised autonomy, as it demonstrates that the company’s Full Self-Driving system has reached sufficient reliability for a broader real-world deployment, which is something the company has worked on extensively.
It also shows Tesla is game for a competition with its rivals in the autonomous ride-hailing sector. Tesla has often matched or exceeded competitors like Waymo in coverage area, despite its smaller fleet. This step highlights Tesla’s iterative, data-driven progress toward a high-margin, app-based Robotaxi network.
It’s not the absolute largest area expansion ever, but achieving full unsupervised operations across a major metro is a key moment in the Robotaxi story. It shifts the program from limited pilot/testing toward a more mature commercial service, while gathering the miles needed for faster growth.
Tesla piggybacks recent Supercharger feature with update that takes it further
Tesla Full Self-Driving v14.3.3 driver monitoring: We tested it
