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SpaceX’s first flight-proven Falcon Heavy Block 5 rocket ready for static fire test
According to NASASpaceflight.com, SpaceX is just ~48 hours away from Falcon Heavy Flight 3’s critical static fire test, in which all 27 of the rocket’s Merlin 1D engines will be briefly ignited.
If the routine test goes as planned, SpaceX’s third completed Falcon Heavy will be ready to lift off as early as 11:30 pm ET (03:30 UTC), June 24th. Atop the massive rocket will be the US Air Force’s Space Test Program-2 (STP-2) mission, a collection of 24 small satellites from a variety of US government agencies and academic institutions. Practically speaking, STP is often more of an engineered excuse to launch, involving satellites and customers that are willing to accept higher risk than more valuable payloads, making it far easier for the US military to certify new technologies and new commercial launch vehicles.
As previously discussed on Teslarati, STP-2 is an extremely ambitious mission that aims to simultaneously certify or pave the way towards certification of critical capabilities. First and foremost, it will (barring serious anomalies) give the US military the data it needs to certify SpaceX’s Falcon Heavy rocket for all national defense launches, giving ULA’s Delta IV Heavy its first real competition in a decade and a half.
Included under the umbrella of that catch-all certification is a sort of torture-test validation of the long-coast capabilities of SpaceX’s Falcon upper stage. To successfully complete STP-2, the upper stage will be subjected to “four separate upper-stage engine burns, three separate deployment orbits, a final propulsive passivation maneuver, and a total mission duration of over six hours.” It will likely be SpaceX’s most technically-challenging launch ever.
Finally, the US Air Force has decided that STP-2 presents an excellent opportunity to begin the process of certifying flight-proven SpaceX rockets for military launches. The STP-2-related work is more of a preliminary effort for the USAF to actually figure out how to certify flight-proven commercial rockets, but it will still be the first time the a dedicated US military mission has flown on a flight-proven launch vehicle. Down the road, the processes set in place thanks – in part – to STP-2 and Falcon Heavy may also apply to aspirational rockets like Blue Origin’s New Glenn and ULA’s “SMART” concept for Vulcan reuse.
Still, New Glenn is unlikely to be ready for flight-proven military launches until the mid-2020s, while ULA has no plans to even attempt to implement Vulcan’s “SMART” reuse until ~2026, meaning that military certification probably wont come until 2028-2030 at the earliest. SpaceX has thus earned roughly half a decade where it will be the only viable US launch provider that can offer certified flight-proven hardware with an established record of reliability. Although the Air Force Research Laboratory (AFRL) had a lone smallsat aboard SpaceX’s February 2019 launch of PSN-6 and Spaceflight’s GTO-1 mission, STP-2 will be the first time a dedicated Department of Defense mission has flown on flight-proven launch vehicle hardware since 1992 (STS-53).
Aside from flight-proven Falcon Heavy side boosters B1052 and B1053, STP-2 is expected to use a new center core, B1057. SpaceX is in the late stages of vehicle integration and should be nearly complete by Monday, June 17th in order to support a June 18th static fire. The specific static fire window is not yet public but Falcon Heavy will likely roll out to Pad 39A no less than 12 hours before.
Teslarati photographers Tom Cross and Pauline Acalin will both be on site with a bevy of remote cameras to capture SpaceX’s third Falcon Heavy before, during, and after liftoff. STP-2 will be Falcon Heavy’s first attempted nighttime launch. Stay tuned for updates as we get closer to T-0!
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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
