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Tesla Smart Summon patent highlights progress in 3D labeling for full self-driving features
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.”
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- A method flow chart from Tesla’s autonomous 3D labeling patent. | Image: Tesla/USPTO
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- A method flow chart from Tesla’s Smart Summon patent application. | Image: Tesla/USPTO
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.
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.
Elon Musk
Elon Musk’s Boring Company opens Vegas Loop’s newest station
The Fontainebleau is the latest resort on the Las Vegas Strip to embrace the tunneling startup’s underground transportation system.
Elon Musk’s tunneling startup, The Boring Company, has welcomed its newest Vegas Loop station at the Fontainebleau Las Vegas.
The Fontainebleau is the latest resort on the Las Vegas Strip to embrace the tunneling startup’s underground transportation system.
Fontainebleau Loop station
The new Vegas Loop station is located on level V-1 of the Fontainebleau’s south valet area, as noted in a report from the Las Vegas Review-Journal. According to the resort, guests will be able to travel free of charge to the stations serving the Las Vegas Convention Center, as well as to Loop stations in Encore and Westgate.
The Fontainebleau station connects to the Riviera Station, which is located in the northwest parking lot of the convention center’s West Hall. From there, passengers will be able to access the greater Vegas Loop.
Vegas Loop expansion
In December, The Boring Company began offering Vegas Loop rides to and from Harry Reid International Airport. Those trips include a limited above-ground segment, following approval from the Nevada Transportation Authority to allow surface street travel tied to Loop operations.
Under the approval, airport rides are limited to no more than four miles of surface street travel, and each trip must include a tunnel segment. The Vegas Loop currently includes more than 10 miles of tunnels. From this number, about four miles of tunnels are operational.
The Boring Company President Steve Davis previously told the Review-Journal that the University Center Loop segment, which is currently under construction, is expected to open in the first quarter of 2026. That extension would allow Loop vehicles to travel beneath Paradise Road between the convention center and the airport, with a planned station located just north of Tropicana Avenue.
News
Tesla leases new 108k-sq ft R&D facility near Fremont Factory
The lease adds to Tesla’s presence near its primary California manufacturing hub as the company continues investing in autonomy and artificial intelligence.
Tesla has expanded its footprint near its Fremont Factory by leasing a 108,000-square-foot R&D facility in the East Bay.
The lease adds to Tesla’s presence near its primary California manufacturing hub as the company continues investing in autonomy and artificial intelligence.
A new Fremont lease
Tesla will occupy the entire building at 45401 Research Ave. in Fremont, as per real estate services firm Colliers. The transaction stands as the second-largest R&D lease of the fourth quarter, trailing only a roughly 115,000-square-foot transaction by Figure AI in San Jose.
As noted in a Silicon Valley Business Journal report, Tesla’s new Fremont lease was completed with landlord Lincoln Property Co., which owns the facility. Colliers stated that Tesla’s Fremont expansion reflects continued demand from established technology companies that are seeking space for engineering, testing, and specialized manufacturing.
Tesla has not disclosed which of its business units will be occupying the building, though Colliers has described the property as suitable for office and R&D functions. Tesla has not issued a comment about its new Fremont lease as of writing.
AI investments
Silicon Valley remains a key region for automakers as vehicles increasingly rely on software, artificial intelligence, and advanced electronics. Erin Keating, senior director of economics and industry insights at Cox Automotive, has stated that Tesla is among the most aggressive auto companies when it comes to software-driven vehicle development.
Other automakers have also expanded their presence in the area. Rivian operates an autonomy and core technology hub in Palo Alto, while GM maintains an AI center of excellence in Mountain View. Toyota is also relocating its software and autonomy unit to a newly upgraded property in Santa Clara.
Despite these expansions, Colliers has noted that Silicon Valley posted nearly 444,000 square feet of net occupancy losses in Q4 2025, pushing overall vacancy to 11.2%.
In Pennsylvania, we got between 10 and 12 inches of snow over the weekend as a nasty Winter storm ripped through a large portion of the country, bringing snow to some areas and nasty ice storms to others.
I have had a Model Y Performance for the week courtesy of Tesla, which got the car to me last Monday. Today was my last full day with it before I take it back to my local showroom, and with all the accumulation on it, I decided to run a cool little experiment: How long would it take for Tesla’s Defrost feature to melt 8 inches of snow?
Tesla’s Defrost feature is one of the best and most underrated that the car has in its arsenal. While every car out there has a defrost setting, Tesla’s can be activated through the Smartphone App and is one of the better-performing systems in my opinion.
It has come in handy a lot through the Fall and Winter, helping clear up my windshield more efficiently while also clearing up more of the front glass than other cars I’ve owned.
The test was simple: don’t touch any of the ice or snow with my ice scraper, and let the car do all the work, no matter how long it took. Of course, it would be quicker to just clear the ice off manually, but I really wanted to see how long it would take.
Tesla Model Y heat pump takes on Model S resistive heating in defrosting showdown
Observations
I started this test at around 10:30 a.m. It was still pretty cloudy and cold out, and I knew the latter portion of the test would get some help from the Sun as it was expected to come out around noon, maybe a little bit after.
I cranked it up and set my iPhone up on a tripod, and activated the Time Lapse feature in the Camera settings.
The rest of the test was sitting and waiting.
It didn’t take long to see some difference. In fact, by the 20-minute mark, there was some notable melting of snow and ice along the sides of the windshield near the A Pillar.
However, this test was not one that was “efficient” in any manner; it took about three hours and 40 minutes to get the snow to a point where I would feel comfortable driving out in public. In no way would I do this normally; I simply wanted to see how it would do with a massive accumulation of snow.
It did well, but in the future, I’ll stick to clearing it off manually and using the Defrost setting for clearing up some ice before the gym in the morning.
Check out the video of the test below:
❄️ How long will it take for the Tesla Model Y Performance to defrost and melt ONE FOOT of snow after a blizzard?
Let’s find out: pic.twitter.com/Zmfeveap1x
— TESLARATI (@Teslarati) January 26, 2026
Elon Musk’s Boring Company opens Vegas Loop’s newest station
Tesla leases new 108k-sq ft R&D facility near Fremont Factory
