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Boeing's astronaut capsule flies off course, fate uncertain after launch debut
Roughly 30 minutes after lifting off for the first time on a United Launch Alliance (ULA) Atlas V rocket, Boeing’s Starliner crew capsule suffered a major failure when it attempted to raise its orbit with onboard engines.
A few hours after the failure came to light, NASA and Boeing held a press conference to update members of the media on the situation, with the space agency offering some candid – if a bit odd – insight into Starliner’s anomalous launch debut. Before the spacecraft’s software threw a wrench into the gears, the plan was for Starliner to separate from ULA’s Atlas V Centaur upper stage and use its own thrusters to reach orbit and begin the trek up Earth’s gravity well to the International Space Station (ISS).
While it will likely take weeks or even months for Boeing and NASA to determine exactly what went wrong during the mission, preliminary information has already begun to paint a fairly detailed picture.
Around 15 minutes after liftoff, Starliner separated from the rocket as intended but it appears that things began to go awry almost immediately afterward. Most notably, according to NASA administrator Jim Bridenstine’s tweets and later comments, a very early look at the telemetry suggests that Starliner’s internal clock was somehow tricked into believing that the time was either earlier or later than it actually was.
Thinking that it was in the midst of a lengthy thruster firing meant to raise its orbit and send the spacecraft on its way to the space station, Starliner was thus focused on ensuring that it was pointed as accurately as possible. Although the space station is the size of a football field, in the vastness of space, rendezvousing with it is a bit like threading a needle. While firing thrusters to do so, spacecraft thus need to point themselves as accurately as possible.
While coasting before or after one of those orbit-boosting thruster firings, Starliner thought it was actually burning towards the space station and was thus very carefully controlling its orientation with a dozen or so smaller thrusters. In short, those unintentional thruster firings burned through a ton of Starliner’s limited propellant supply – enough to make it impossible (or nearly so) for the spacecraft to rendezvous and dock the ISS, a central purpose of this particular launch.
This ultimately means that Starliner is leaning heavily on the “test” aspect of this Orbital Flight Test (OFT), uncovering failure modes and bugs that Boeing was clearly unable to tease out with ground testing and simulation. While in a totally different ballpark, SpaceX similar Crew Dragon spacecraft suffered its own major failure earlier this year, although that capsule explosion occurred during intentional ground testing, whereas Starliner’s software failed during its high-profile launch debut and has severely curtailed the scope of the spacecraft’s first orbital flight test.
In fact, Bridenstine was unable to rule out the possibility that Boeing will have to attempt a second uncrewed orbital flight test (OFT) before Starliner will be qualified to launch the space agency’s astronauts. Although early signs suggest that Boeing will still be able to attempt to deorbit and recover the spacecraft a day or two from now, the fact that Starliner will not be able to perform critical demonstrations of its ISS rendezvous and docking capabilities will make it far harder for NASA to rationally certify the spacecraft for astronaut launches.
SpaceX’s Crew Dragon, for reference, completed a more or less flawless launch, orbit raise, and rendezvous before docking with the ISS. It’s almost impossible to imagine NASA giving SpaceX permission to proceed immediately into its first astronaut launch if Crew Dragon had failed to reach the proper orbit or dock with the space station.
Regardless, it’s far too early to tell whether Boeing will have to repeat Starliner’s OFT. If Starliner performs absolutely perfectly between now and its planned soft-landing in New Mexico, there might be a chance that NASA will still allow Boeing to effectively cut corners to its astronaut launch debut, but only time will tell.
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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
