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SpaceX launches 52nd Falcon 9 rocket in 52 weeks
SpaceX has completed its 52nd successful Falcon 9 launch in 52 weeks, sustaining an average cadence of one launch per week for a full 12 months.
Simultaneously, the Starlink 4-2 rideshare mission set a new record for Falcon 9 booster reuse, marked SpaceX’s 150th consecutively successful launch, and was one of the most complex commercial launches it has ever performed.
In addition to 34 new Starlink V1.5 satellites that joined almost 3000 other working SpaceX spacecraft in orbit, Starlink 4-2 deployed the company’s largest rideshare payload yet – AST SpaceMobile’s 1.5-ton (~3300 lb) BlueWalker 3 communications satellite.
Falcon 9 lifted off on schedule with the combined 12-ton (~26,500 lb) payload safely secured inside its composite payload fairing at 9:20 pm EDT (01:20 UTC) on Saturday, September 10th. Tasked with lifting the rocket’s expendable upper stage, recoverable fairing, and payload most of the way out of Earth’s atmosphere was Falcon 9 booster B1058, a nine-engine first stage that debuted by launching two NASA astronauts in May 2020.
28 months later, B1058 lifted off with Starlink 4-2 and BlueWalker 3 on its 14th spaceflight and orbital-class launch, breaking Falcon 9’s booster reuse record. The rocket performed no differently than it had every time previously, burning for a bit less than three minutes before deploying the upper stage and returning to Earth. About nine minutes after liftoff, B1058 safely touched down on drone ship A Shortfall Of Gravitas (ASOG), likely setting the booster up to break its own record before the end of 2022. With 13 launches already under their belts, boosters B1051 and B1060 will likely follow B1058 past the same 14-flight milestone in the near future.
Once free from the booster, Falcon 9’s expendable upper stage kicked off SpaceX’s most complex commercial launch ever. Measuring about six minutes long, the first and longest burn brought the second stage and payload into an elliptical orbit a few hundred kilometers above Earth’s surface. A second burn followed about 45 minutes after liftoff, raising the low end of that ellipse to deploy BlueWalker 3 into a circular orbit around 500 kilometers (~310 mi). Using a massive antenna, AST SpaceMobile’s first large satellite prototype will eventually attempt to directly communicate with mobile phones to provide a level of connectivity equivalent to 5G/LTE – all from space.
Once free of its rideshare payload, the focus shifted to Starlink. In theory, SpaceX could have taken the easy way out and significantly simplified the mission by deploying all 34 satellites at the same altitude as BlueWalker 3, simultaneously allowing them to reach their operational 540-kilometer (~336 mi) orbits in days instead of months. Instead, SpaceX pursued an exceptionally complex mission requiring five burns from Falcon 9’s upper stage.
After deploying BlueWalker 3, Falcon 9 S2 lowered one end of its orbit at around T+67 minutes, followed by a fourth burn to lower the other end almost two hours after liftoff. The upper stage then spun up end over end and eventually released all 34 Starlink satellites at an altitude of ~335 kilometers (~208 mi), where debris and faulty satellites will take days – rather than years – to reenter Earth’s atmosphere and burn up.
While SpaceX doesn’t confirm post-payload operations, Falcon 9 S2 was also scheduled to perform a fifth and final burn to quickly deorbit itself, ensuring that the mission only produced five pieces of benign debris. At their very low orbits, those five pieces (four ‘tensioning rods’ and the BlueWalker 3 payload adapter) will pose next to no threat to other spacecraft or rockets and should reenter within a few weeks.
Starlink 4-2 was SpaceX’s 52nd successful Falcon 9 launch since September 14th, 2021, meaning that the company has technically already achieved CEO Elon Musk’s goal of 52 launches in one year – albeit not a calendar year. Perhaps even more impressive, the mission was SpaceX’s 150th consecutively successful Falcon launch. No other single rocket (Falcon 9) or rocket family (Falcon) has launched more times in a row without failure.
Finally, Starlink 4-2 was SpaceX’s 42nd launch of 2022. If the company continues its average cadence over the last three months, it could end 2022 having completed more than 60 Falcon launches in one calendar year.
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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.
Elon Musk
Elon Musk’s Grok records lowest hallucination rate in AI reliability study
Grok achieved an 8% hallucination rate, 4.5 customer rating, 3.5 consistency, and 0.07% downtime, resulting in an overall risk score of just 6.
A December 2025 study by casino games aggregator Relum has identified Elon Musk’s Grok as one of the most reliable AI chatbots for workplace use, boasting the lowest hallucination rate at just 8% among the 10 major models tested.
In comparison, market leader ChatGPT registered one of the highest hallucination rates at 35%, just behind Google’s Gemini, which registered a high hallucination rate of 38%. The findings highlight Grok’s factual prowess despite the AI model’s lower market visibility.
Grok tops hallucination metric
The research evaluated chatbots on hallucination rate, customer ratings, response consistency, and downtime rate. The chatbots were then assigned a reliability risk score from 0 to 99, with higher scores indicating bigger problems.
Grok achieved an 8% hallucination rate, 4.5 customer rating, 3.5 consistency, and 0.07% downtime, resulting in an overall risk score of just 6. DeepSeek followed closely with 14% hallucinations and zero downtime for a stellar risk score of 4. ChatGPT’s high hallucination and downtime rates gave it the top risk score of 99, followed by Claude and Meta AI, which earned reliability risk scores of 75 and 70, respectively.
Why low hallucinations matter
Relum Chief Product Officer Razvan-Lucian Haiduc shared his thoughts about the study’s findings. “About 65% of US companies now use AI chatbots in their daily work, and nearly 45% of employees admit they’ve shared sensitive company information with these tools. These numbers show well how important chatbots have become in everyday work.
“Dependence on AI tools will likely increase even more, so companies should choose their chatbots based on how reliable and fit they are for their specific business needs. A chatbot that everyone uses isn’t necessarily the one that works best for your industry or gives accurate answers for your tasks.”
In a way, the study reveals a notable gap between AI chatbots’ popularity and performance, with Grok’s low hallucination rate positioning it as a strong choice for accuracy-critical applications. This was despite the fact that Grok is not used as much by users, at least compared to more mainstream AI applications such as ChatGPT.
NVIDIA Director of Robotics: Tesla FSD v14 is the first AI to pass the “Physical Turing Test”
Tesla AI team burns the Christmas midnight oil by releasing FSD v14.2.2.1
