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SpaceX Falcon 9 Block 5 booster ends launch #2 with spectacular dawn return
SpaceX Falcon 9 booster B1049 has completed its second successful launch and landing with a spectacular dawn return to Port of Los Angeles, where engineers and technicians will work to remove the rocket’s grid fins and landing legs and prepare the vehicle for transport to the company’s Hawthorne, CA factory and refurbishment facilities.
Once post-recovery processing is complete and B1049 is safe and snug inside one of SpaceX’s refurbishment facilities, the booster can be expected to be ready to perform its next (third) orbital-class mission perhaps just 2-3 months from now, whether or not there is a mission that needs its support.
Just Read the Instructions has now docked, carrying twice-flown Iridium-8 booster. Beautiful sunrise arrival. #spacex pic.twitter.com/OAi77wm3XT
— Pauline Acalin (@w00ki33) January 13, 2019
Just ~48 hours after the Block 5 booster’s second successful launch and landing, this time aboard drone ship Just Read The Instructions (JRTI) after supporting the historic Iridium-8 mission, JRTI pulled into Port of Los Angeles with Falcon 9 in tow, backlit by a picturesque California sunrise. In September 2018, the same booster (B1049) successfully completed its launch debut from SpaceX’s LC-40 launch pad in Cape Canaveral, Florida before landing safely aboard drone ship Of Course I Still Love You (OCISLY).
This marks the second time ever that a Falcon 9 booster has launched from both coasts (Cape Canaveral, FL and Vandenberg, CA) and landed on both SpaceX drone ships (JRTI and OCISLY), an event that will likely become increasingly common as the company’s growing fleet of Falcon 9 Block 5 boosters become increasingly flexible and interchangeable. It’s also equally possible that – over time – a sort of regional fleet of Falcon 9s will ultimately accumulate at each of SpaceX’s three launch pads, ensuring that there is always a rocket ready and waiting to launch a customer payload with short notice and minimal production or refurbishment-related delays.
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- Falcon 9 B1049 and a few SpaceX recovery technicians serve as an excellent since of scale for launch photos. (Pauline Acalin)
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- Falcon 9 B1049 returned to Port of Los Angeles after its second successful launch and landing in four months. (Pauline Acalin)
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- Falcon 9 B1049 seen vertical at SLC-4E prior to its second launch, the eighth and final Iridium NEXT mission. (SpaceX)
Among many of Falcon 9’s almost sculpture-like qualities, Teslarati photographer Pauline Acalin’s photos of the booster’s return exemplify just how reliably unperturbed Block 5 appears after performing multiple orbital-class launches, far from a rocket that traveled to ~90 km (~56 mi) while reaching speeds of 1.9 kilometers per second (6830 km/h, 4300 mph). SpaceX now reliably reuses Falcon 9’s titanium grid fins and landing legs with little to no refurbishment or touching up between launches and should eventually be able to retract the rocket’s legs after recovery, further cutting down on processing and refurbishment times.
Greater reusability, greater reliability?
As of today, it’s unclear how big of a role Falcon 9 Block 5 booster refurbishment has played into several hardware-readiness-related delays to several recent flight-proven Falcon 9 launches (SSO-A, SAOCOM 1A, and Iridium-8), but it is ultimately a fundamental reality of all manufacturing that rushing or ‘expediting’ work will typically hurt product quality and reliability and generally widen the cracks that mistakes can slip through. Interestingly, having a truly large fleet of flight-proven Falcon 9 Block 5 rockets on hand could dramatically improve the overall launch-readiness of Falcon 9 and Falcon Heavy and minimize chances of processing delays across the board.
SpaceX employees may already be to a point where they can plausible take stock of the company’s already-significant fleet of flight-proven Falcon 9s (B1046-B1049) to decide which booster is closest to launch-readiness before assigning it to a given mission. With four proven boosters on hand as of January 2019, options are fairly limited and regionality is likely to factor heavily into which booster launches which mission – there is no real cushion if problems arise with a given rocket or its preceding launch suffers its own delays. However, once that Falcon fleet grows to something like 10 or 15 booster, SpaceX could conceivably be able to guarantee booster availability regardless of prior launch delays or a given rocket’s condition after landing.
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- (Pauline Acalin)
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- A bittersweet sunrise as Falcon 9 B1049 arrives in port. (Pauline Acalin)
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- (Pauline Acalin)
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- (Pauline Acalin)
This may well be far less sexy than SpaceX’s ultimate goal of drop-of-the-pin, 24-hour reusability for Falcon and BFR boosters, but the fundamental fact of the matter is that the company may well be able to derive a vast majority of that practice’s value by simply having a large, well-kept fleet of Falcon 9 boosters that are at least moderately reusable. For a hefty chunk of the probable near-term future, a large fleet of rockets each capable of launching every 30-60 days would likely be able to support launch cadences that are currently unprecedented for a single company or rocket (i.e. dozens of launches per year).
Time is money, of course, so minimizing the turnaround time of Falcon boosters will ultimately remain a major priority, especially as the prospect of Starlink launches loom.
For prompt updates, on-the-ground perspectives, and unique glimpses of SpaceX’s rocket recovery fleet check out our brand new LaunchPad and LandingZone newsletters!
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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
