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Tesla designs safer airbag deployment system through seat sensors in new patent
Tesla’s electric cars are among the safest on the road, so much so that the Model 3, Model S, and Model X are among the NHTSA’s top vehicles with the lowest probability of injury in the event of an accident. Thanks to Tesla’s use of ultra-high-strength steel and aluminum, as well as the vehicles’ extra large crumple zones due to their all-electric design, the company’s electric cars are capable of protecting their occupants when untoward events happen on the road.
If a recently published patent application is any indication, though, it appears that Tesla is exploring more ways to make its vehicles even safer. Tesla’s recent patent, titled “Sensors for Vehicle Occupant Classification Systems and Methods,” taps into the company’s prowess in tech by using a system that alows cars to detect and/or classify their occupants based on readings from a series of sensors in the seats. With such a system in place, safety features could activate in a way that is optimized for passengers.
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- Diagrams depicting Tesla’s “Sensors for Vehicle Occupant Classification Systems and Methods” patent. (Credit: US Patent Office)
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- Diagrams depicting Tesla’s “Sensors for Vehicle Occupant Classification Systems and Methods” patent. (Credit: US Patent Office)
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- Diagrams depicting Tesla’s “Sensors for Vehicle Occupant Classification Systems and Methods” patent. (Credit: US Patent Office)
Diagrams depicting Tesla’s “Sensors for Vehicle Occupant Classification Systems and Methods” patent. (Credit: US Patent Office)
Tesla notes that cars on the road today are becoming safer overall, thanks to systems that monitor operations while the vehicle is in motion and features that provide coordinated alerts and assistance as needed. While such processes make vehicles safe, though, Tesla states that there is still a large area for improvement. One such area, according to the electric car maker, is in the way airbags deploy in the event of an accident.
“Difficulties remain in reliably detecting the presence of vehicle occupants and accurately classifying them as children, relatively small adults, and/or according to other classifications, and particularly in differentiating between classifications. Accurate classification can be critical when the vehicle is attempting to assist or enact safety measures to protect the occupant.
“In particular, airbag deployment can be adjusted to reduce risk of injury caused by the airbag while maintaining safety of the occupant during a collision. However, while reduced-force airbag deployment is recommended for relatively small adult females, it is not recommended for young children, even though the young children can reach heights and weights approaching those of the relatively small adult females. Thus, there is a need for an improved methodology to provide reliable and accurate vehicle occupant classification, particularly in the context of controlling an occupant restraint system that can apply force to an operator of the vehicle.”
Tesla’s patent application explores the use of sensors placed on the vehicle’s seats that enable the cars to classify their occupants. By classifying the size, weight, and body type (among others) of a passenger, the car would be able to deploy airbags in the safest way possible during an accident. Tesla describes this system as follows.
“In accordance with various embodiments of the present disclosure, occupant detection and classification may be provided by an occupant weight sensor, an occupant presence sensor, and a logic device configured to convert sensor signals provided by the occupant weight sensor and the occupant presence sensor into an estimated occupant weight and an occupant presence response, which may be used together to reliably detect and classify the occupant with increased sensitivity, accuracy, and granularity compared to conventional detection systems.
“In particular, embodiments of the present occupant classification system may be employed to detect and differentiate a child from a relatively small woman or man and disable, partially enable, or fully enable an airbag as appropriate. Such occupant classification systems may be implemented with various types of user feedback mechanisms, including reporting detections and classifications both locally and remotely, such as to a smartphone, for example, and reporting potentially unsafe conditions and/or undesired operation of the vehicle, as described herein.”
With this system in place, Tesla’s electric cars would be even safer than they already are. If any, this would widen the gap further between Tesla’s vehicles and conventional cars, many of which are bogged down in frontal collisions due to the presence of a large, heavy engine under the hood. That said, this recent patent application all but emphasizes Tesla’s proactive nature and the company’s tendency to always make efforts to improve.
This particular nature was emphasized by Elon Musk on Twitter last October, when he explained that there is “no such thing” as a “full refresh” or even a model year at Tesla. In his tweet, Musk stated that all the company’s vehicles are partially upgraded every month “as soon as a subsystem is ready for production,” thereby ensuring buyers that they are getting the best vehicles available at their time of purchase. This, coupled with Tesla’s trademark over-the-air updates — which give new features from driver assist functions such as Navigate on Autopilot, to fun, quirky things like the Romance Mode Easter Egg — truly make the company’s electric cars unique on the road.
The full text of Tesla’s recent patent application could be accessed here.
Elon Musk
Starlink passes 9 million active customers just weeks after hitting 8 million
The milestone highlights the accelerating growth of Starlink, which has now been adding over 20,000 new users per day.
SpaceX’s Starlink satellite internet service has continued its rapid global expansion, surpassing 9 million active customers just weeks after crossing the 8 million mark.
The milestone highlights the accelerating growth of Starlink, which has now been adding over 20,000 new users per day.
9 million customers
In a post on X, SpaceX stated that Starlink now serves over 9 million active users across 155 countries, territories, and markets. The company reached 8 million customers in early November, meaning it added roughly 1 million subscribers in under seven weeks, or about 21,275 new users on average per day.
“Starlink is connecting more than 9M active customers with high-speed internet across 155 countries, territories, and many other markets,” Starlink wrote in a post on its official X account. SpaceX President Gwynne Shotwell also celebrated the milestone on X. “A huge thank you to all of our customers and congrats to the Starlink team for such an incredible product,” she wrote.
That growth rate reflects both rising demand for broadband in underserved regions and Starlink’s expanding satellite constellation, which now includes more than 9,000 low-Earth-orbit satellites designed to deliver high-speed, low-latency internet worldwide.
Starlink’s momentum
Starlink’s momentum has been building up. SpaceX reported 4.6 million Starlink customers in December 2024, followed by 7 million by August 2025, and 8 million customers in November. Independent data also suggests Starlink usage is rising sharply, with Cloudflare reporting that global web traffic from Starlink users more than doubled in 2025, as noted in an Insider report.
Starlink’s momentum is increasingly tied to SpaceX’s broader financial outlook. Elon Musk has said the satellite network is “by far” the company’s largest revenue driver, and reports suggest SpaceX may be positioning itself for an initial public offering as soon as next year, with valuations estimated as high as $1.5 trillion. Musk has also suggested in the past that Starlink could have its own IPO in the future.
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NVIDIA Director of Robotics: Tesla FSD v14 is the first AI to pass the “Physical Turing Test”
After testing FSD v14, Fan stated that his experience with FSD felt magical at first, but it soon started to feel like a routine.
NVIDIA Director of Robotics Jim Fan has praised Tesla’s Full Self-Driving (Supervised) v14 as the first AI to pass what he described as a “Physical Turing Test.”
After testing FSD v14, Fan stated that his experience with FSD felt magical at first, but it soon started to feel like a routine. And just like smartphones today, removing it now would “actively hurt.”
Jim Fan’s hands-on FSD v14 impressions
Fan, a leading researcher in embodied AI who is currently solving Physical AI at NVIDIA and spearheading the company’s Project GR00T initiative, noted that he actually was late to the Tesla game. He was, however, one of the first to try out FSD v14.
“I was very late to own a Tesla but among the earliest to try out FSD v14. It’s perhaps the first time I experience an AI that passes the Physical Turing Test: after a long day at work, you press a button, lay back, and couldn’t tell if a neural net or a human drove you home,” Fan wrote in a post on X.
Fan added: “Despite knowing exactly how robot learning works, I still find it magical watching the steering wheel turn by itself. First it feels surreal, next it becomes routine. Then, like the smartphone, taking it away actively hurts. This is how humanity gets rewired and glued to god-like technologies.”
The Physical Turing Test
The original Turing Test was conceived by Alan Turing in 1950, and it was aimed at determining if a machine could exhibit behavior that is equivalent to or indistinguishable from a human. By focusing on text-based conversations, the original Turing Test set a high bar for natural language processing and machine learning.
This test has been passed by today’s large language models. However, the capability to converse in a humanlike manner is a completely different challenge from performing real-world problem-solving or physical interactions. Thus, Fan introduced the Physical Turing Test, which challenges AI systems to demonstrate intelligence through physical actions.
Based on Fan’s comments, Tesla has demonstrated these intelligent physical actions with FSD v14. Elon Musk agreed with the NVIDIA executive, stating in a post on X that with FSD v14, “you can sense the sentience maturing.” Musk also praised Tesla AI, calling it the best “real-world AI” today.
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Tesla AI team burns the Christmas midnight oil by releasing FSD v14.2.2.1
The update was released just a day after FSD v14.2.2 started rolling out to customers.
Tesla is burning the midnight oil this Christmas, with the Tesla AI team quietly rolling out Full Self-Driving (Supervised) v14.2.2.1 just a day after FSD v14.2.2 started rolling out to customers.
Tesla owner shares insights on FSD v14.2.2.1
Longtime Tesla owner and FSD tester @BLKMDL3 shared some insights following several drives with FSD v14.2.2.1 in rainy Los Angeles conditions with standing water and faded lane lines. He reported zero steering hesitation or stutter, confident lane changes, and maneuvers executed with precision that evoked the performance of Tesla’s driverless Robotaxis in Austin.
Parking performance impressed, with most spots nailed perfectly, including tight, sharp turns, in single attempts without shaky steering. One minor offset happened only due to another vehicle that was parked over the line, which FSD accommodated by a few extra inches. In rain that typically erases road markings, FSD visualized lanes and turn lines better than humans, positioning itself flawlessly when entering new streets as well.
“Took it up a dark, wet, and twisty canyon road up and down the hill tonight and it went very well as to be expected. Stayed centered in the lane, kept speed well and gives a confidence inspiring steering feel where it handles these curvy roads better than the majority of human drivers,” the Tesla owner wrote in a post on X.
Tesla’s FSD v14.2.2 update
Just a day before FSD v14.2.2.1’s release, Tesla rolled out FSD v14.2.2, which was focused on smoother real-world performance, better obstacle awareness, and precise end-of-trip routing. According to the update’s release notes, FSD v14.2.2 upgrades the vision encoder neural network with higher resolution features, enhancing detection of emergency vehicles, road obstacles, and human gestures.
New Arrival Options also allowed users to select preferred drop-off styles, such as Parking Lot, Street, Driveway, Parking Garage, or Curbside, with the navigation pin automatically adjusting to the ideal spot. Other refinements include pulling over for emergency vehicles, real-time vision-based detours for blocked roads, improved gate and debris handling, and Speed Profiles for customized driving styles.
Starlink passes 9 million active customers just weeks after hitting 8 million
NVIDIA Director of Robotics: Tesla FSD v14 is the first AI to pass the “Physical Turing Test”
