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SpaceX Starship prototype gearing up for first static fire with three Raptor engines
Two days after Elon Musk announced that Starship SN8 “passed cryo proof” testing, SpaceX has begun installing three Raptor engines on the rocket for the first multi-Raptor static fire ever attempted.
On October 9th, the CEO revealed that the first SpaceX Starship prototype bound for a crucial high-altitude test flight had successfully completed cryogenic proof testing after four full nights of work. Curiously, Musk didn’t say much else but past comments indicated that SpaceX would follow up a successful Starship SN8 cryo proof test by installing three Raptors for the first attempt at a historic engine testing milestone: the multi-engine static fire.
Recently discussed on Teslarati, Starship SN8 was the first flightworthy prototype to have functional aerodynamic control surfaces (flaps) installed, a milestone SpaceX passed on September 23rd. The rocket was rolled to the launch pad three days later but forced to sit at the pad for four days until high winds died down, at which point SpaceX was able to install SN8 on the launch mount.
“If SN8 reaches the necessary pressure and survives the stress of its cryo proof(s), it will likely become the first Starship to attempt a triple-Raptor static fire – a first for the engine, too. Starship SN8’s first cryo proof attempt is scheduled no earlier than 9pm-6am CDT (UTC-5) on Sunday, October 4th with backup windows on the 5th and 6th. The first static fire attempt – possibly beginning with one Raptor or jumping straight to three – could happen several days after a successful cryo proof.
According to Elon Musk, SpaceX will static fire SN8 twice before attempting its 15 km (~50,000 ft) launch debut. More likely than not, SpaceX will attempt a triple-engine static fire with the Starship as-is, install SN8’s nosecone and forward flaps, and attempt a second static fire while only drawing propellant from the rocket’s smaller header tanks (one of which is located in the tip of its nose). Only time (or Elon tweets) will tell.”
Teslarati.com — October 1st, 2020
As speculated on October 1st, it appears that SpaceX will indeed proceed with Raptor static fire testing before installing Starship SN8’s nose section, reducing the schedule impact and cost of a hypothetical failure. Although modern computer simulations are far better than they used to be, there is still always some inherent risk present during the first multi-engine static fire of a rocket, as operating multiple rocket engines in close proximity can produce complex interactions that are hard to predict.
Based on the fact that SpaceX has already shipped two Raptors to the launch pad, it looks like Starship SN8 will begin static fire testing with three engines installed, although there’s still a chance SpaceX will sequentially proceed through one, two, and three-Raptor tests.
Regardless, SpaceX has yet to file for road closures for Starship SN8’s first static fire test campaign. Based on past tests with Starships SN4, SN5, and SN6, the first static fire attempt could happen just a few days to a week after engine installation and will be preceded by at least one or two wet dress rehearsals (WDRs) and Raptor ‘spin prime’ and/or preburner tests. Per Musk, after the first successful static fire, SpaceX will inspect the rocket (and likely install its nose section) before performing another static fire to clear Starship SN8 for flight. Stay tuned for updates!
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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”
