News
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.”
- A method flow chart from Tesla’s autonomous 3D labeling patent. | Image: Tesla/USPTO
- 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.
News
SpaceX Starship Flight 13 faces wrath of the Texas skies
SpaceX pushed Starship Flight 13 to Friday, blaming weather instead of the previous engine issues.
SpaceX called off Thursday’s launch attempt of Starship Flight 13, pushing the mission to Friday because of weather tied to Tropical Storm Bertha. The company confirmed the delay on X, noting “Now targeting Friday, July 24 for Starship’s thirteenth flight test, due to weather. A key objective for the flight test is to get clear imagery from the ground of Starship’s heatshield as it flies at a higher dynamic pressure during ascent, which won’t be possible with today’s weather conditions.”
This is the second delay for Flight 13 in two weeks. SpaceX first tried to launch the mission on July 16, but the countdown ended in an automated abort at T-0 when four of Super Heavy Booster 20’s 33 Raptor engines failed to ignite. Musk said at the time that two Raptors would need to be removed and replaced, as Teslarati reported. The company spent the following week destacking Ship 40 and Booster 20, swapping engines, and running leak checks before restacking the vehicle on Pad 2 Wednesday night, according to Spaceflight Now’s live coverage.
Unlike the engine problem, Thursday’s delay has nothing to do with the hardware. SpaceX wants clean footage of Starship’s heat shield captured from the ground as the vehicle flies through max dynamic pressure, something the storm’s cloud cover over South Texas would not allow. The company said visibility should improve for Friday’s attempt, with the same 90 minute window opening at 5:45 p.m. CT.
Flight 13 will be the second outing for the V3 versions of Starship and Super Heavy, following their debut on Flight 12 in May. The mission carries 20 production Starlink V3 satellites, the first time SpaceX has flown operational satellites rather than mass simulators on Starship. Six of those satellites are fitted with cameras to inspect the heat shield from a different angle during ascent, giving engineers a second data source beyond the ground imagery the weather is currently blocking.
Booster 20 will attempt a boostback burn and a splashdown landing burn in the Gulf of America, while Ship 40 follows a suborbital trajectory toward a landing in the Indian Ocean. The flight plan largely mirrors Flight 12, though the booster will run a more aggressive ascent burn after max Q this time, and the ship’s heat shield includes load sensing tiles meant to measure stress at the higher dynamic pressure SpaceX is targeting.
If Friday’s attempt succeeds, Flight 13 could be the last suborbital test in the program. SpaceX is already looking to push for an orbital flight on Flight 14.
Investor's Corner
Tesla stock tumbles after earnings, one of its sharpest single-day declines
Tesla stock (NASDAQ: TSLA) endured one of its sharpest single-day declines in years on July 23, tumbling approximately 14.5 percent and closing near $320 after opening the session around $374. The drop erased more than $140 billion in market value amid heavy trading volume and left the shares at multi-week lows.
The sell-off followed the company’s second-quarter 2026 results, released the previous evening. Tesla reported record revenue of $28.2 billion, up 26 percent year over year, driven by a Q2-record 480,126 vehicle deliveries. Energy storage deployments also rose strongly.
Tesla (TSLA) Q2 2026 earnings results: miss on EPS, beat on revenue
Yet profitability disappointed sharply. Operating income fell 57 percent to $398 million, compressing the operating margin to just 1.4 percent. Non-GAAP earnings per share came in at $0.33, well below the roughly $0.53 analysts had expected. Free cash flow turned negative by $1.1 billion as capital expenditures surged 142 percent to $5.8 billion, largely tied to accelerated spending on artificial intelligence, robotics, and autonomous systems.
The losses on capex were expected, as Tesla said it would be spending heavily in 2026.
Investors also reacted to lingering uncertainty surrounding key product timelines. During the Earnings Call, management reiterated ambitions for Robotaxi deployment and the Optimus humanoid robot, but offered limited new concrete milestones, renewing questions about execution pace that have long accompanied Tesla’s ambitious roadmap.
The magnitude of the decline places it among Tesla’s more severe one-day percentage losses since its 2010 initial public offering. Historically, the two largest single-day drops (split-adjusted) remain September 8, 2020, when shares fell 21.1 percent amid broader market volatility and valuation concerns, and January 13, 2012, with a 19.3 percent plunge during the company’s early growth struggles.
Other notable declines include an 18.6 percent drop on March 16, 2020, at the onset of pandemic-related market turmoil. Thursday’s move ranks roughly ninth on the all-time list but stands out as the steepest in more than a year.
Despite the short-term pain, Tesla’s long-term trajectory has repeatedly recovered from such volatility. The latest results underscore both the strength of its core automotive and energy businesses and the near-term costs of heavy investment in next-generation technologies.
Elon Musk
Elon Musk is not happy about this Tesla Full Self-Driving approval delay
Elon Musk clapped back at France’s decision to withhold the approval for Tesla’s Full Self-Driving (FSD) Supervised system, projecting a clear and blunt message to French Transport Minister Phillippe Tabarot, after he publicly rejected the technology in its current form.
Tabarot outlines several concerns with Tesla Full Self-Driving in a detailed video statement, where he said, “The safety trade-offs are not yet sufficient to authorize it as it currently stands,” he said. He emphasized that FSD is not a true self-driving system and that the driver remains fully responsible.
Key issues Tabarot also brought up included allowing speeding when surrounding traffic exceeds limits and what he believes are insufficient guarantees of driver attention during complex urban maneuvers such as lane changes, intersections, and roundabouts.
Delaying the approval of FSD in France will cost lives
— Elon Musk (@elonmusk) July 22, 2026
While acknowledging technological progress and France’s support for autonomous innovation, Tabarot stressed that deployment must prioritize road safety. He noted ongoing technical discussions with Tesla, the Netherlands, and other European partners, with further ecosystem meetings planned for the fall.
Musk’s rebuke highlights the human cost of regulatory caution. Tesla’s latest safety reports provide compelling data supporting accelerated adoption. In the most recent 12-month period, vehicles using FSD (Supervised) recorded one major collision per approximately 5.1 million miles driven, dramatically better than the U.S. national average of one crash per 698,000 miles.
Even Tesla vehicles driven manually with active safety features outperform the average by a wide margin. These figures come from billions of real-world miles of telemetry, showing FSD vehicles involved in far fewer incidents than both manual Teslas and the broader U.S. fleet.
Critics argue Tesla’s comparisons require careful scrutiny regarding reporting thresholds and fleet demographics, yet the data consistently positions FSD as a potential lifesaver. With road fatalities remaining a leading cause of death worldwide, Musk contends that proven safer technology should not face prolonged bureaucratic hurdles.
France’s measured approach reflects the broader European regulatory caution, which many, especially Musk, have been critical of in the past. However, as autonomous systems from Tesla and competitors like Waymo demonstrate superior safety in independent studies, pressure is mounting for harmonized approvals.
Musk’s warning carries the belief that every month of delay may equate to avoidable tragedies on European roads.

