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SpaceX delays Starhopper’s first flight a few days despite Raptor preburner test success
SpaceX has (partially) ignited Starhopper’s freshly-installed Raptor engine, successfully verifying that the engine is ready for its next major test: a full ignition and static firing. Although successful, SpaceX still has some work to do before the vehicle is ready for its first untethered flight(s).
July 15th’s progress is just the latest in a several day-series of preflight tests designed to reduce the likelihood that Starhopper is destroyed over the coming days and (hopefully) weeks. If all goes planned during the awkward Starship prototype’s first foray into hover tests, SpaceX CEO Elon Musk has stated that he will provide an official presentation updating the public on the status of the company’s ever-changing next-generation rocket.
The past week or so of Starhopper preflight testing began with Raptor serial number 6 (SN06) completing the last of a series of acceptance test fires in McGregor, Texas on June 10th. Even on its own, this was a major milestone for the new SpaceX engine: Raptor SN06 was the first of the new, full-scale engines to pass the acceptance test program with flying colors. According to Musk, for the engine to complete those tests so successfully, SpaceX had to solve a challenging bug in which some sort of mechanical resonance (i.e. vibration) damaged or destroyed Raptors SN01-05.
Hours later, the engine began a short ~450 mi (720 km) journey south to Starhopper, located in Boca Chica, Texas. The engine arrived on July 11th and was fully installed on Starhopper by the following evening (July 12th), at which point SpaceX put Starhopper and Raptor through some mild but valuable thrust vector controller (TVC) tests, wiggling the car-sized engine to ensure it can accurately steer the prototype rocket.
Around two days after the above ‘wiggle’ test was successfully completed, SpaceX moved into the next stage, partially fueling Starhopper with liquid methane and oxygen propellant and helium pressurant in what is known in rocketry as a wet dress rehearsal (WDR). The (implicitly) successful WDR was capped off with a duo of what can now safely be concluded were some sort of Raptor test preceding even pre-ignition operations. Whatever the tests were, they appear to have been completed successfully.
That appears to be the case because less than 24 hours after their completion, on July 15th, SpaceX once again began loading Starhopper with propellant and pressurant for a second round of wet testing. This time around, SpaceX got right into more critical Raptor tests once enough propellant was loaded, igniting the engine’s interwoven oxygen and methane preburners.

Previously discussed 24 hours ago in a Teslarati article focused on Raptor wiggles and other miscellaneous tests, Raptor is an extremely advanced rocket engine based on a cycle (i.e. how propellant is turned into thrust) known as full-flow staged combustion.
“In a staged-combustion engine like Raptor, getting from the supercool liquid oxygen and methane propellant to 200+ tons of thrust is quite literally staged, meaning that the ignition doesn’t happen all at once. Rather, the preburners – essentially their own, unique combustion chambers – ignite an oxygen- or methane-rich mixture, the burning of which produces the gas and pressure that powers the turbines that bring fuel into the main combustion chamber. That fuel then ignites, producing thrust as they exit the engine’s bell-shaped nozzle.
Unintuitively, conditions inside the preburner – hidden away from view – are actually far more intense than the iconic blue, purple, and pink flame that visibly exists Raptor’s nozzle. Much like hot water will cool while traveling through pipes, the superheated gaseous propellant that Raptor ignites to produce thrust will also cool (and thus lose pressure) as it travels from Raptor’s preburner to its main combustion chamber. If the pressure produced in the preburners is too low, Raptor’s thrust will be (roughly speaking) proportionally limited at best. At worst, low pressure in the preburners can trigger a “hard start” or shutdown that could destroy the engine. According to Elon Musk, Raptor’s oxygen preburner thus has the worst of it, operating at pressures as high or higher than 800 bar (11,600 psi, 80 megapascals).”
In full-flow staged combustion (FFSC), even more complexity is added as all propellant that touches the engine must necessarily end up traveling through the main combustion chamber to eke every last ounce of thrust out of the finite propellant a rocket lifts off with. As such, FFSC engines can be about as efficient as the laws of physics allow any given chemical rocket engine to be, at the cost of exceptional complexity and brutally difficult development.
Additionally, FFSC physically requires two separate preburners and then makes things even harder by making each separate preburner (methane and oxygen) depend on each other’s operation for the engine to fully ignite. This means that no individual preburner can be used to kickstart Raptor – instead, SpaceX must somehow spin the turbopumps that feed propellant into each preburner with some separate system. This is all just to emphasize the fact that Raptor’s ignition sequence is a spectacularly complex orchestra of valves, spark plugs, sensors, and magic. This is why it’s valuable for Raptor to test its preburner system independently of an actual ignition test, at least as long as the engine is still in the development stages.

According to NASASpaceflight.com managing editor Chris Bergin, what this practically translates to is a minor Starhopper hover test delay of 1-2 days, while the static fire has also been pushed roughly 24 hours from July 15th to July 16th. If that full static fire produces lots of happy data, Starhopper could be cleared for a hover test debut attempt as early as Wednesday or Thursday (July 17/18).
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Tesla FSD v14.2.2 is getting rave reviews from drivers
So far, early testers have reported buttery-smooth drives with confident performance, even at night or on twisty roads.
Tesla Full Self-Driving (Supervised) v14.2.2 is receiving positive reviews from owners, with several drivers praising the build’s lack of hesitation during lane changes and its smoother decision-making, among others.
The update, which started rolling out on Monday, also adds features like dynamic arrival pin adjustment. So far, early testers have reported buttery-smooth drives with confident performance, even at night or on twisty roads.
Owners highlight major improvements
Longtime Tesla owner and FSD user @BLKMDL3 shared a detailed 10-hour impression of FSD v14.2.2, noting that the system exhibited “zero lane change hesitation” and “extremely refined” lane choices. He praised Mad Max mode’s performance, stellar parking in locations including ticket dispensers, and impressive canyon runs even in dark conditions.
Fellow FSD user Dan Burkland reported an hour of FSD v14.2.2’s nighttime driving with “zero hesitations” and “buttery smooth” confidence reminiscent of Robotaxi rides in areas such as Austin, Texas. Veteran FSD user Whole Mars Catalog also demonstrated voice navigation via Grok, while Tesla owner Devin Olsen completed a nearly two-hour drive with FSD v14.2.2 in heavy traffic and rain with strong performance.
Closer to unsupervised
FSD has been receiving rave reviews, even from Tesla’s competitors. Xpeng CEO He Xiaopeng, for one, offered fresh praise for FSD v14.2 after visiting Silicon Valley. Following extended test drives of Tesla vehicles running the latest FSD software, He stated that the system has made major strides, reinforcing his view that Tesla’s approach to autonomy is indeed the proper path towards autonomy.
According to He, Tesla’s FSD has evolved from a smooth Level 2 advanced driver assistance system into what he described as a “near-Level 4” experience in terms of capabilities. While acknowledging that areas of improvement are still present, the Xpeng CEO stated that FSD’s current iteration significantly surpasses last year’s capabilities. He also reiterated his belief that Tesla’s strategy of using the same autonomous software and hardware architecture across private vehicles and robotaxis is the right long-term approach, as it would allow users to bypass intermediate autonomy stages and move closer to Level 4 functionality.
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Elon Musk’s Grok AI to be used in U.S. War Department’s bespoke AI platform
The partnership aims to provide advanced capabilities to 3 million military and civilian personnel.
The U.S. Department of War announced Monday an agreement with Elon Musk’s xAI to embed the company’s frontier artificial intelligence systems, powered by the Grok family of models, into the department’s bespoke AI platform GenAI.mil.
The partnership aims to provide advanced capabilities to 3 million military and civilian personnel, with initial deployment targeted for early 2026 at Impact Level 5 (IL5) for secure handling of Controlled Unclassified Information.
xAI Integration
As noted by the War Department’s press release, GenAI.mil, its bespoke AI platform, will gain xAI for the Government’s suite of tools, which enable real-time global insights from the X platform for “decisive information advantage.” The rollout builds on xAI’s July launch of products for U.S. government customers, including federal, state, local, and national security use cases.
“Targeted for initial deployment in early 2026, this integration will allow all military and civilian personnel to use xAI’s capabilities at Impact Level 5 (IL5), enabling the secure handling of Controlled Unclassified Information (CUI) in daily workflows. Users will also gain access to real‑time global insights from the X platform, providing War Department personnel with a decisive information advantage,” the Department of War wrote in a press release.
Strategic advantages
The deal marks another step in the Department of War’s efforts to use cutting-edge AI in its operations. xAI, for its part, highlighted that its tools can support administrative tasks at the federal, state and local levels, as well as “critical mission use cases” at the front line of military operations.
“The War Department will continue scaling an AI ecosystem built for speed, security, and decision superiority. Newly IL5-certified capabilities will empower every aspect of the Department’s workforce, turning AI into a daily operational asset. This announcement marks another milestone in America’s AI revolution, and the War Department is driving that momentum forward,” the War Department noted.
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Tesla FSD (Supervised) v14.2.2 starts rolling out
The update focuses on smoother real-world performance, better obstacle awareness, and precise end-of-trip routing, among other improvements.
Tesla has started rolling out Full Self-Driving (Supervised) v14.2.2, bringing further refinements to its most advanced driver-assist system. The new FSD update focuses on smoother real-world performance, better obstacle awareness, and precise end-of-trip routing, among other improvements.
Key FSD v14.2.2 improvements
As noted by Not a Tesla App, 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 let users select preferred drop-off styles, such as Parking Lot, Street, Driveway, Parking Garage, or Curbside, with the navigation pin automatically adjusting to the user’s ideal spot for precision.
Other additions include pulling over for emergency vehicles, real-time vision-based detours for blocked roads, improved gate and debris handling, and extreme Speed Profiles for customized driving styles. Reliability gains cover fault recovery, residue alerts on the windshield, and automatic narrow-field camera washing for new 2026 Model Y units.
FSD v14.2.2 also boosts unprotected turns, lane changes, cut-ins, and school bus scenarios, among other things. Tesla also noted that users’ FSD statistics will be saved under Controls > Autopilot, which should help drivers easily view how much they are using FSD in their daily drives.
Key FSD v14.2.2 release notes
Full Self-Driving (Supervised) v14.2.2 includes:
- Upgraded the neural network vision encoder, leveraging higher resolution features to further improve scenarios like handling emergency vehicles, obstacles on the road, and human gestures.
- Added Arrival Options for you to select where FSD should park: in a Parking Lot, on the Street, in a Driveway, in a Parking Garage, or at the Curbside.
- Added handling to pull over or yield for emergency vehicles (e.g. police cars, fire trucks, ambulances).
- Added navigation and routing into the vision-based neural network for real-time handling of blocked roads and detours.
- Added additional Speed Profile to further customize driving style preference.
- Improved handling for static and dynamic gates.
- Improved offsetting for road debris (e.g. tires, tree branches, boxes).
- Improve handling of several scenarios, including unprotected turns, lane changes, vehicle cut-ins, and school buses.
- Improved FSD’s ability to manage system faults and recover smoothly from degraded operation for enhanced reliability.
- Added alerting for residue build-up on interior windshield that may impact front camera visibility. If affected, visit Service for cleaning!
- Added automatic narrow field washing to provide rapid and efficient front camera self-cleaning, and optimize aerodynamics wash at higher vehicle speed.
- Camera visibility can lead to increased attention monitoring sensitivity.
Upcoming Improvements:
- Overall smoothness and sentience.
- Parking spot selection and parking quality.