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Tesla Smart Summon patent highlights progress in 3D labeling for full self-driving features

Tesla Smart Summon in action. (Credit: Rody Davis/YouTube)

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A recently published Tesla patent application details the machine learning methods behind Smart Summon, specifically highlighting the progress being made with 3D labeling in training data.

The application, titled “Autonomous and User Controlled Vehicle Summon to a Target,” utilizes machine learning methods explicitly detailed in two other recent Tesla patent publications in its functionality. This series of three inventions altogether describes an automated way of generating training data which is then used by a machine learning model to accomplish an expansive list of self-driving capabilities in Summon.

“Traditionally, much of the effort to curate a training data set is done manually by reviewing potential training data and properly labeling the features associated with the data,” Tesla’s first application in the series states. “The effort required to create a training set with accurate labels can be significant and is often tedious… Therefore, there exists a need to improve the process for generating training data with accurate labeled features.”

The application goes on to describe how labeled training data is made autonomously in their invention using sensors and the collection of what’s called a “time series,” i.e., a series of images captured over a period of time.

“Using data captured by sensors on a vehicle to capture the environment of the vehicle and vehicle operating parameters, a training data set is created,” it explains. “In some embodiments, a three-dimensional representation of a feature, such as a lane line, is created from the group of time series elements that corresponds to the ground truth… As one example, a series of images for a time period, such as 30 seconds, is used to determine the actual path of a vehicle lane line over the time period the vehicle travels…a single image of the group and the actual path taken can be used as training data to predict the path of the vehicle.”

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Tesla CEO Elon Musk has previously mentioned that better labeling is one of the keys to speeding up the rollout of self-driving functionality and features like Reverse Summon. “We need to finish work on Autopilot core foundation code & 3D labeling, then functionality will happen quickly. Not long now,” Musk wrote on Twitter in March this year. With better labeling (more accurate training data) comes safer and more capable software due to improved predictions from the modeling.

Tesla Owners Silicon Valley Smart Summon Model 3s (Credit: @MinimalDuck)

When it comes to Tesla’s Smart Summon, prediction modeling is essential considering there isn’t a driver in the vehicle during its operation. The patent publication covering Summon embodies the first application’s time series functionality and a second application’s implementation of the time series’ training data in its methods, demonstrating one of the numerous potential uses for the machine learning invention. Hints about future developments using Smart Summon are also detailed in the application. Examples include:

  • Syncing the Smart Summon with a calendar so the vehicle “automatically navigates to arrive at the location at the ending time, such as the end of a dinner party, a wedding, a restaurant reservation, etc.”
  • Implementing a multi-part destination into the Summon instructions such as waypoints at an airport to pick up multiple passengers.
  • Monitoring the heartbeat of a Summon user to ensure they are maintaining a connection with the vehicle while operating the feature.
  • Customizing the vehicle’s arrival settings such as interior lighting, exterior lighting, hazard lights, welcome music, and climate control preferences.

One of the more unique bits about the Smart Summon patent application is the appearance of Elon Musk as an inventor. While the CEO is known to be intimately involved in nearly all aspects of vehicle design, software features, and business operations, his name is unexpectedly absent from most of the company’s inventions. However, this is apparently on purpose. “I generally try my best not to be on patents,” he revealed on Twitter in reply to a post about the Smart Summon application. Notably, inventorship is a legal definition based on the conception of an invention, i.e., not the person/people who suggested or directed its creation, but the person/people who devised the means to accomplish it.

Prior to the most recent patent publication, Musk contributed inventorship to the door and body styling of the Model X. He also contributed the same to both the design and function of Tesla’s vehicle charge inlets.

Accidental computer geek, fascinated by most history and the multiplanetary future on its way. Quite keen on the democratization of space. | It's pronounced day-sha, but I answer to almost any variation thereof.

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Tesla Robotaxi’s biggest rival sends latest statement with big expansion

The new expanded geofence now covers a broader region of Austin and its metropolitan areas, extended south to Manchaca and north beyond US-183.

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Credit: @AdanGuajardo/X

Tesla Robotaxi’s biggest rival sent its latest statement earlier this month by making a big expansion to its geofence, pushing the limits up by over 50 percent and nearing Tesla’s size.

Waymo announced earlier this month that it was expanding its geofence in Austin by slightly over 50 percent, now servicing an area of 140 square miles, over the previous 90 square miles that it has been operating in since July 2025.

Tesla CEO Elon Musk shades Waymo: ‘Never really had a chance’

The new expanded geofence now covers a broader region of Austin and its metropolitan areas, extended south to Manchaca and north beyond US-183.

These rides are fully driverless, which sets them apart from Tesla slightly. Tesla operates its Robotaxi program in Austin with a Safety Monitor in the passenger’s seat on local roads and in the driver’s seat for highway routes.

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It has also tested fully driverless Robotaxi services internally in recent weeks, hoping to remove Safety Monitors in the near future, after hoping to do so by the end of 2025.

Although Waymo’s geofence has expanded considerably, it still falls short of Tesla’s by roughly 31 square miles, as the company’s expansion back in late 2025 put it up to roughly 171 square miles.

There are several differences between the two operations apart from the size of the geofence and the fact that Waymo is able to operate autonomously.

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Waymo emphasizes mature, fully autonomous operations in a denser but smaller area, while Tesla focuses on more extensive coverage and fleet scaling potential, especially with the potential release of Cybercab and a recently reached milestone of 200 Robotaxis in its fleet across Austin and the Bay Area.

However, the two companies are striving to achieve the same goal, which is expanding the availability of driverless ride-sharing options across the United States, starting with large cities like Austin and the San Francisco Bay Area. Waymo also operates in other cities, like Las Vegas, Los Angeles, Orlando, Phoenix, and Atlanta, among others.

Tesla is working to expand to more cities as well, and is hoping to launch in Miami, Houston, Phoenix, Las Vegas, and Dallas.

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Tesla automotive will be forgotten, but not in a bad way: investor

It’s no secret that Tesla’s automotive division has been its shining star for some time. For years, analysts and investors have focused on the next big project or vehicle release, quarterly delivery frames, and progress in self-driving cars. These have been the big categories of focus, but that will all change soon.

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(Credit: Tesla)

Entrepreneur and Angel investor Jason Calacanis believes that Tesla will one day be only a shade of how it is recognized now, as its automotive side will essentially be forgotten, but not in a bad way.

It’s no secret that Tesla’s automotive division has been its shining star for some time. For years, analysts and investors have focused on the next big project or vehicle release, quarterly delivery frames, and progress in self-driving cars. These have been the big categories of focus, but that will all change soon.

I subscribed to Tesla Full Self-Driving after four free months: here’s why

Eventually, and even now, the focus has been on real-world AI and Robotics, both through the Full Self-Driving and autonomy projects that Tesla has been working on, as well as the Optimus program, which is what Calacanis believes will be the big disruptor of the company’s automotive division.

On the All-In podcast, Calcanis revealed he had visited Tesla’s Optimus lab earlier this month, where he was able to review the Optimus Gen 3 prototype and watch teams of engineers chip away at developing what CEO Elon Musk has said will be the big product that will drive the company even further into the next few decades.

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Calacanis said:

“Nobody will remember that Tesla ever made a car. They will only remember the Optimus.”

He added that Musk “is going to make a billion of those.”

Musk has stated this point himself, too. He at one point said that he predicted that “Optimus will be the biggest product of all-time by far. Nothing will even be close. I think it’ll be 10 times bigger than the next biggest product ever made.”

He has also indicated that he believes 80 percent of Tesla’s value will be Optimus.

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Optimus aims to totally revolutionize the way people live, and Musk has said that working will be optional due to its presence. Tesla’s hopes for Optimus truly show a crystal clear image of the future and what could be possible with humanoid robots and AI.

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Tesla Robotaxi fleet reaches new milestone that should expel common complaint

There have been many complaints in the eight months that the Robotaxi program has been active about ride availability, with many stating that they have been confronted with excessive wait times for a ride, as the fleet was very small at the beginning of its operation.

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Credit: Tesla

Tesla Robotaxi is active in both the Bay Area of California and Austin, Texas, and the fleet has reached a new milestone that should expel a common complaint: lack of availability.

It has now been confirmed by Robotaxi Tracker that the fleet of Tesla’s ride-sharing vehicles has reached 200, with 158 of those being available in the Bay Area and 42 more in Austin. Despite the program first launching in Texas, the company has more vehicles available in California.

The California area of operation is much larger than it is in Texas, and the vehicle fleet is larger because Tesla operates it differently; Safety Monitors sit in the driver’s seat in California while FSD navigates. In Texas, Safety Monitors sit in the passenger’s seat, but will switch seats when routing takes them on the highway.

Tesla has also started testing rides without any Safety Monitors internally.

Tesla Robotaxi goes driverless as Musk confirms Safety Monitor removal testing

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This new milestone confronts a common complaint of Robotaxi riders in Austin and the Bay, which is vehicle availability.

There have been many complaints in the eight months that the Robotaxi program has been active about ride availability, with many stating that they have been confronted with excessive wait times for a ride, as the fleet was very small at the beginning of its operation.

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With that being said, there have been some who have said wait times have improved significantly, especially in the Bay, where the fleet is much larger.

Tesla’s approach to the Robotaxi fleet has been to prioritize safety while also gathering its footing as a ride-hailing platform.

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Of course, there have been and still will be growing pains, but overall, things have gone smoothly, as there have been no major incidents that would derail the company’s ability to continue developing an effective mode of transportation for people in various cities in the U.S.

Tesla plans to expand Robotaxi to more cities this year, including Miami, Las Vegas, and Houston, among several others.

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