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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 (TSLA) receives “Buy” rating and $551 PT from Canaccord Genuity

He also maintained a “Buy” rating for TSLA stock over the company’s improving long-term outlook, which is driven by autonomy and robotics.

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Credit: Tesla China

Canaccord Genuity analyst George Gianarikas raised his Tesla (NASDAQ:TSLA) price target from $482 to $551. He also maintained a “Buy” rating for TSLA stock over the company’s improving long-term outlook, which is driven by autonomy and robotics. 

The analyst’s updated note

Gianarikas lowered his 4Q25 delivery estimates but pointed to several positive factors in the Tesla story. He noted that EV adoption in emerging markets is gaining pace, and progress in FSD and the Robotaxi rollout in 2026 represent major upside drivers. Further progress in the Optimus program next year could also add more momentum for the electric vehicle maker. 

“Overall, yes, 4Q25 delivery expectations are being revised lower. However, the reset in the US EV market is laying the groundwork for a more durable and attractive long-term demand environment. 

“At the same time, EV penetration in emerging markets is accelerating, reinforcing Tesla’s potential multi‑year growth runway beyond the US. Global progress in FSD and the anticipated rollout of a larger robotaxi fleet in 2026 are increasingly important components of the Tesla equity story and could provide sentiment tailwinds,” the analyst wrote. 

Tesla’s busy 2026

The upcoming year would be a busy one for Tesla, considering the company’s plans and targets. The autonomous two-seat Cybercab has been confirmed to start production sometime in Q2 2026, as per Elon Musk during the 2025 Annual Shareholder Meeting.

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Apart from this, Tesla is also expected to unveil the next-generation Roadster on April 1, 2026. Tesla is also expected to start high-volume production of the Tesla Semi in Nevada next year. 

Apart from vehicle launches, Tesla has expressed its intentions to significantly ramp the rollout of FSD to several regions worldwide, such as Europe. Plans are also underway to launch more Robotaxi networks in several more key areas across the United States.

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Waymo sues Santa Monica over order to halt overnight charging sessions

In its complaint, Waymo argued that its self-driving cars’ operations do not constitute a public nuisance, and compliance with the city’s order would cause the company irreparable harm.

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Credit: Waymo

Waymo has filed a lawsuit against the City of Santa Monica in Los Angeles County Superior Court, seeking to block an order that requires the company to cease overnight charging at two facilities. 

In its complaint, Waymo argued that its self-driving cars’ operations do not constitute a public nuisance, and compliance with the city’s order would cause the company irreparable harm.

Nuisance claims

As noted in a report from the Los Angeles Times, Waymo’s two charging sites at Euclid Street and Broadway have operated for about a year, supporting the company’s growing fleet with round-the-clock activity. Unfortunately, this has also resulted in residents in the area reportedly being unable to sleep due to incessant beeping from self-driving taxis that are moving in and out of the charging stations around the clock. 

Frustrated residents have protested against the Waymos by blocking the vehicles’ paths, placing cones, and “stacking” cars to create backups. This has also resulted in multiple calls to the police.

Last month, the city issued an order to Waymo and its charging partner, Voltera, to cease overnight operations at the charging locations, stating that the self-driving vehicles’ activities at night were a public nuisance. A December 15 meeting yielded no agreement on mitigations like software rerouting. Waymo proposed changes, but the city reportedly insisted that nothing would satisfy the irate residents.

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“We are disappointed that the City has chosen an adversarial path over a collaborative one. The City’s position has been to insist that no actions taken or proposed by Waymo would satisfy the complaining neighbors and therefore must be deemed insufficient,” a Waymo spokesperson stated.

Waymo pushes back

In its legal complaint, Waymo stated that its “activities at the Broadway Facilities do not constitute a public nuisance.” The company also noted that it “faces imminent and irreparable harm to its operations, employees, and customers” from the city’s order. The suit also stated that the city was fully aware that the Voltera charging sites would be operating around the clock to support Waymo’s self-driving taxis.

The company highlighted over one million trips in Santa Monica since launch, with more than 50,000 rides starting or ending there in November alone. Waymo also criticized the city for adopting a contentious strategy against businesses. 

“The City of Santa Monica’s recent actions are inconsistent with its stated goal of attracting investment. At a time when the City faces a serious fiscal crisis, officials are choosing to obstruct properly permitted investment rather than fostering a ‘ready for business’ environment,” Waymo stated. 

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Tesla FSD v14.2.2 is getting rave reviews from drivers

So far, early testers have reported buttery-smooth drives with confident performance, even at night or on twisty roads.

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Credit: @BLKMDL3/X

Tesla Full Self-Driving (Supervised) v14.2.2 is receiving positive reviews from owners, with several drivers praising the build’s lack of hesitation during lane changes and its smoother decision-making, among others. 

The update, which started rolling out on Monday, also adds features like dynamic arrival pin adjustment. So far, early testers have reported buttery-smooth drives with confident performance, even at night or on twisty roads.

Owners highlight major improvements

Longtime Tesla owner and FSD user @BLKMDL3 shared a detailed 10-hour impression of FSD v14.2.2, noting that the system exhibited “zero lane change hesitation” and “extremely refined” lane choices. He praised Mad Max mode’s performance, stellar parking in locations including ticket dispensers, and impressive canyon runs even in dark conditions.

Fellow FSD user Dan Burkland reported an hour of FSD v14.2.2’s nighttime driving with “zero hesitations” and “buttery smooth” confidence reminiscent of Robotaxi rides in areas such as Austin, Texas. Veteran FSD user Whole Mars Catalog also demonstrated voice navigation via Grok, while Tesla owner Devin Olsen completed a nearly two-hour drive with FSD v14.2.2 in heavy traffic and rain with strong performance.

Closer to unsupervised

FSD has been receiving rave reviews, even from Tesla’s competitors. Xpeng CEO He Xiaopeng, for one, offered fresh praise for FSD v14.2 after visiting Silicon Valley. Following extended test drives of Tesla vehicles running the latest FSD software, He stated that the system has made major strides, reinforcing his view that Tesla’s approach to autonomy is indeed the proper path towards autonomy.

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According to He, Tesla’s FSD has evolved from a smooth Level 2 advanced driver assistance system into what he described as a “near-Level 4” experience in terms of capabilities. While acknowledging that areas of improvement are still present, the Xpeng CEO stated that FSD’s current iteration significantly surpasses last year’s capabilities. He also reiterated his belief that Tesla’s strategy of using the same autonomous software and hardware architecture across private vehicles and robotaxis is the right long-term approach, as it would allow users to bypass intermediate autonomy stages and move closer to Level 4 functionality.

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