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SpaceX CEO Elon Musk says first orbital Starship prototype will be done by June
SpaceX CEO Elon Musk says that the company’s first Starship prototype – a low-fidelity hop test vehicle – has finished assembly in South Texas, paving the way towards a series of experimental vertical take-off or landing (VTOL) hop tests that could begin as early as February or March 2019.
One step beyond the prototype currently rising out of the coastal Texas wetlands, Musk also indicated that the first orbital Starship prototype – essentially the spacecraft’s first full-fidelity test article – could be completed as early as June 2019, a truly extraordinary pace of development for a program as complex and cutting-edge as BFR.
Starship test flight rocket just finished assembly at the @SpaceX Texas launch site. This is an actual picture, not a rendering. pic.twitter.com/k1HkueoXaz
— Elon Musk (@elonmusk) January 11, 2019
Starhopper rising
Barely six weeks after work began on the massive Starship prototype, SpaceX’s Starhopper appears to have grown to its full ~40m (~130 ft) height in South Texas. Following a preliminary fit test on Tuesday, January 8th, workers made a second attempt on Wednesday and completed the final attachment of Starhopper’s upper and lower halves. Intriguingly, no time was wasted spot-welding the halves together after their successful docking, and an additional sheet of stainless steel has been welded over the seam in the hours since then.
- It remains to be seen if BFR can be made as reusable and reliable as it will need to be to sustainably support interplanetary humans. (SpaceX)
- Eventually, SpaceX may graduate into high-speed, high-altitude flight tests of the prototype spaceship to fully test the design of its its control surfaces and “ultra-lightweight heat shield”. (SpaceX)
- (SpaceX)
- BFR’s booster, now known as Super Heavy. (SpaceX)
- BFR (2018) breaks through a cloud layer shortly after launch. (SpaceX)
However, what looks like 9m-diameter (~30 ft) steel tank domes are being assembled and welded together at the same SpaceX facility, despite the fact that no domes have been observed being installed inside Starhopper. Musk did seem to indicate that even Starhopper – requiring far less propellant than an orbital Starship – will still feature full 9m (~30 foot) diameter tanks. This could imply that the newly integrated Starhopper has yet to have propellant tank domes installed inside and will need to be taken apart again to allow for that critical final step. If that is not the case, the only possible explanation is that Starhopper’s propellant tanks will actually be less than 9m in diameter and will be lifted up through the vehicle’s aft for installation.
One last increasingly improbable possibility is that a significant portion of the hopper’s upper half will be or already is a pressure vessel capable of holding cryogenic propellant, although the process of actually watching the less than surgical fabrication does not inspire a great deal of confidence in any potential pressure vessel aspirations. In the meantime, we have been given the first look at what the outside of Starhopper will look like once complete. According to SpaceX CEO Elon Musk, hop tests of the imposing vehicle could begin as few as 4-8 weeks from now.
- Starhopper is assembled for the second time, January 9th. (NSF – bocachicagal)
- And voila! (NSF – bocachicagal)
- Meanwhile, giant 9m-diameter tank domes are being assembled and welded together a few hundred feet away from Starhopper. (NSF – bocachicagal)
To orbit, and beyond!
Aside from offering the above photo and comparing Starhopper’s prospects to those of Falcon 9’s Grasshopper and F9R hop test articles (i.e. very suborbital and very short-lived), Musk also stated that the first orbital Starship prototype could be completed as early as June 2019, as few as three months after Starhopper’s first hop test. This paints at least a rough picture of the planning going on for BFR’s flight test regime, beginning with a suborbital hop test prototype, moving to a full-fidelity Starship capable of high-speed intra-atmospheric heat shield and aero surface testing, and finally full-up orbital testing with the completion of the first BFR booster (now known as Super Heavy).
Should be done with first orbital prototype around June
— Elon Musk (@elonmusk) January 11, 2019
Both, but demo Starship is being built now, whereas Super Heavy hardware will start getting built in spring
— Elon Musk (@elonmusk) December 9, 2018
According to Musk, the first Super Heavy booster will begin production and assembly as early as spring 2019, while the CEO stated that he believed the odds of BFR (Starship/Super Heavy) reaching orbit by 2020 were 60% and “growing rapidly” thanks to a recent move from carbon composite tankage to stainless steel. If SpaceX and Musk keep putting their money where their mouths are and rapidly building test articles and prototypes, that orbital debut might actually be less insane than it sounds. We’ll find out soon enough.
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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.
News
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.








