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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.”

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.

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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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Elon Musk

Tesla CEO Elon Musk denies ridiculous Gigafactory Shanghai rumor

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(Credit: Tesla)

Tesla CEO Elon Musk took to his social media platform X on Thursday night to deny a ridiculous rumor regarding the sale of the company’s Chinese vehicle production plant, Gigafactory Shanghai.

On Thursday, the Wall Street Journal, citing sources familiar with the matter, claimed in a scathing new report that Tesla was exploring a potential sale of the entire China business in an effort to help bolster a potential merger between SpaceX and Tesla.

Musk immediately denied the rumor not once but twice, initially calling it “fake news,” and then calling it “absurdly fake news” in a separate post just a few moments later:

The original poster of the Wall Street Journal article that Musk saw deleted the initial post sharing the headline and the rumored sale of Tesla’s China business.

The report seemed absolutely and unequivocally false to begin with; Tesla’s business in China is among the most important pieces of the company’s business. Not only does the factory supply vehicles for the domestic market, but also for various other markets in Asia and Europe.

China is also one of the largest automotive markets in the world, and Tesla has performed well there despite the robust competition.

The speculation regarding a Tesla and SpaceX merger has started to gain steam this year as the space exploration company went public just a month ago. There has been speculation that Musk will bridge all of his companies under one “umbrella company,” and analysts believe this could happen before the end of the decade.

The Tesla and SpaceX merger everyone is talking about is quietly building

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This is the latest iteration of Musk’s very evident war on mainstream media. Reports regarding any of Musk’s companies are quick to get the dreaded “false” or “fake news” response from the CEO when they are unfounded.

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Tesla AI boss reveals how big Optimus is going to get

Tesla’s Optimus chief corrected himself on X, confirming a staggering 10 million robot production target.

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Tesla Optimus Gen 3 [Credit: Tesla]

Tesla’s Optimus program has a new number attached to it, after Ashok Elluswamy, the executive who has run the humanoid robot program since June 2025, posted a three word correction on X Thursday, “Correction, 10 million robots.”

The line clarifies the long term annual capacity Tesla is building toward its planned second Optimus production line at Gigafactory Texas, a figure Musk has cited repeatedly since last year’s shareholder meeting.

The scale is worth noting, because ten million robots a year would mean Tesla building more units annually than most countries sell in new cars. Tesla has framed this as a second line, not the first. The buildout is happening in two phases: a roughly one million unit per year line inside Tesla’s Fremont factory, installed on the floor space vacated when Model S and Model X production ended earlier this year, and a much larger dedicated facility under construction at Giga Texas that broke ground on its first steel structure in May. That Texas facility is the one Elluswamy’s correction refers to, and is expected to reach volume production sometime in 2027.

Tesla Optimus project fires up as Musk sees production line progress

Elluswamy took over Optimus from Milan Kovac last summer and has spent the months since talking up the program’s trajectory. Elon Musk has also floated the ten million figure at Tesla’s 2025 shareholder meeting.

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Ending Model S and Model X production to make room for the first Optimus line was one of the more consequential manufacturing decisions in the company’s recent history, retiring two flagship vehicles in favor of a robot that has yet to enter mass production. Musk has previously estimated per unit production costs at $20,000 to $25,000 once Tesla reaches a million units a year, though he hasn’t said what that cost looks like at ten times the volume.

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Autonomous vehicle red tape gets slashed by Trump Administration

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Credit: Zoox

The Trump Administration today made several key moves to help with the deployment of autonomous vehicles by cutting overreaching red tape that has stifled growth and innovation for years.

The moves, which were put forth by the National Highway Traffic Safety Administration (NHTSA), aim to grant temporary exemptions to at least one company currently, although that could expand in the coming months. Additionally, it will work with organizations to develop standards and a sound but efficient regulatory landscape.

Zoox is the only company mentioned explicitly by the Trump Administration in its press release announcing the new terms today. They will receive a temporary two-year exemption that will allow the commercial deployment of up to 2,500 vehicles annually for two years.

There is a potential exemption for Robomart, Inc., which “requests a temporary exemption from certain FMVSS No. 500 requirements for a low-speed vehicle operated by an ADS without a human driver onboard. NHTSA will publish a separate notice seeking public comment on its merits once the initial evaluation is complete,” the agency said.

Here are the five new terms that Secretary Sean Duffy has implemented through the NHTSA today:

  1. Allow Zoox to commercially deploy its robotaxis through a temporary exemption.
    This temporary exemption will allow the commercial deployment of up to 2,500 vehicles annually for two years, subject to an enhanced, adaptable oversight structure that can evolve as Zoox’s technology advances.
  2. Accelerate development of first-ever AV performance standards through a partnership with SAE Industry Technologies Consortia (ITC).
    This partnership will fund a three-year, $5 million “A2SCEND” consortium, bringing together experts to gather data and accelerate creation of the first-ever AV performance standards. This project will inform a single national standard for AV safety to eliminate the patchwork regulatory landscape that has stifled innovation for years.
  3. Publish an interim final rule that allows vehicles manufactured prior to an exemption to be eligible for a commercial deployment exemption.
    This rule will modernize the application process and improve access to exemptions for innovators, including AV developers, by granting the NHTSA Administrator the discretion to apply temporary exemptions to vehicles manufactured prior to the effective date of an exemption grant.
  4. Streamline the application process for Part 555 exemptions by updating guidance and soliciting feedback from the public.
    By updating the Part 555 exemption process—which allows automakers to temporarily sell a limited number of non-compliant vehicles, primarily to test new technologies—NHTSA is aiming to create a more flexible oversight structure for exemptions and summarize recent AV framework activities, including expanded exemption pathways, streamlined crash reporting, and ongoing efforts to modernize Federal Motor Vehicle Safety Standards (FMVSS).
  5. Establish a new Federal Docket for public feedback on NHTSA’s updated safe AV development and deployment guidance.
    NHTSA is updating its technical guidance for AVs for the first time since 2017—focusing on key safety areas like emergency responder interactions, safety management systems, remote assistance, and post-crash behavior to help the industry scale up driverless deployments safely.

Additionally, the NHTSA said it has modernized some safety standards by proposing updates to:

  • FMVSS 102 – Transmission shifting
  • FMVSS 103/104 – Windshield defrosting and wiping
  • FMVSS 110 – Tire placards
  • FMVSS 135 – Braking systems
  • FMVSS 101 – Controls and displays
  • FMVSS 108 – Vehicle lighting
  • FMVSS 111 – Mirrors and rearview display
  • FMVSS 126 – Electronic stability control systems
  • FMVSS 201/208 – Sun visors and warning labels

These changes aim to make the regulatory process for autonomous vehicles more streamlined and efficient, which could help the U.S. gain dominance over autonomous vehicle systems moving forward.

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