Tesla will reportedly use teleoperations as an extra safety measure when it first deploys its driverless taxi and ride-hailing service, according to an investor’s note from one firm this morning.
On Tuesday, following a meeting with Tesla’s Investor Relations Head Travis Axelrod, Deutsche Bank wrote in a note that the company expects to need teleoperations, at least at first, as an additional safety measure to back the Cybercab’s camera-based self-driving system. The Cybercab, which was unveiled during a Southern California event in October, doesn’t include a steering wheel or pedals, and is based on the company’s Supervised Full Self-Driving (FSD) software, utilizing only cameras and real-time driving scenarios to train its AI neural network to make driving decisions.
“Tesla believes it would be reasonable to assume some type of teleoperator would be needed at least initially for safety/redundancy purposes,” the firm wrote in a Monday note (via Reuters).
Tesla has not responded to Teslarati’s request to confirm the claim or provide additional details.
READ MORE ABOUT THE CYBERCAB: Tesla’s Elon Musk reveals why Cybercab, Cybertruck don’t equip company logos
Tesla Cybercab: fewer parts, autonomy from driving to charging
Teslarati was one of the first few to take a ride in the Cybercab at Tesla’s October 10 “We, Robot” event, which took place at a Warner Brothers studio in Burbank, California. You can get a close-up look at the two-seat Cybercab in our coverage of the event below.
?: Our FULL first ride in the @Tesla Cybercab pic.twitter.com/6gR7OgKRCz
— TESLARATI (@Teslarati) October 11, 2024
Beyond touting the scalability of its FSD software, due to its utilization of a neural network model unlike other companies that are subject to geofencing and pre-mapping, Tesla has regularly highlighted the lower-cost cameras its products use as a major savings benefit compared to companies that use LiDAR and multiple redundant systems at once. While redundancy may be important to Tesla at first with the use of teleoperation, the company is looking long-term at a non-redundant camera-based system used in its other vehicles, which has already been gathering training data from real drivers over the years.
Earlier this month, Tesla’s Principal Mechanical Design Engineer Eric Earley said that the Cybercab has roughly half the parts of a Model 3, highlighting the massive cost-savings the company expects to gain from production of the autonomous vehicle.
“Two seats unlocks a lot of opportunity aerodynamically. It also means we cut the part count of Cybercab down by a substantial margin. We’re gonna be delivering a car that has roughly half the parts of Model 3 today,” Earley said. “It also means when you need to clean the car as a rideshare asset, you really don’t have to worry about navigating multiple doors, multiple seats. You really just have what looks like a bench seat, easy to clean automatically.”
Eventually, Tesla aims to produce two million Cybercabs per year, and in addition to being fully driverless, the company has also shared plans for a wireless charging system, and an autonomous cleaning robot, both of which are expected to allow the vehicle to be completely independent of human input, even beyond driving.
Tesla spotted testing Cybercab in Giga Texas premises
What are your thoughts? Let me know at zach@teslarati.com, find me on X at @zacharyvisconti, or send us tips at tips@teslarati.com.


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.
News
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.