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SpaceX simulates lifting Starship with launch tower ‘arms’
SpaceX has taken Starbase’s rocket-catching launch tower ‘arms’ to new heights during the latest series of proof tests.
That process began in earnest on January 4th, when SpaceX lifted, opened, and swung the tower’s building-sized arms for the first time. Four days later, SpaceX performed a variation on the first round of tests, again slowly lifting the assembly up the side of the launch tower and opening and closing the arms. The most notable difference was the addition of several tandem swing tests, which hinted at more applied tests that were soon to come. SpaceX also performed some basic tests with a third Starship fueling arm higher up on the tower, very slowly swinging it towards where Starship would be standing.
On Sunday afternoon, a third major round of testing kicked off. This set of tests was considerably more focused than the prior two, suggesting that it was more of a simulation of the main purpose of the arms.
Instead of lifting a few dozen feet and performing basic actuation and coordination tests, SpaceX simply lifted the arm assembly up along the tower’s exterior and didn’t stop. There were a few temporary pauses but the arms ultimately reached the approximate height they’d need to reach to stack a Starship on top of a Super Heavy booster. In fact, despite being (in)famous for being partially designed to catch boosters and ships out of mid-air, the main purpose of the arms – and likely the only reason they exist at all – is to safely, accurately, and precisely lift, install, and stack Starships and Super Heavy boosters.
SpaceX could obviously use a giant crawler or tower crane to accomplish a similar feat but cranes – especially large and tall ones – are extremely sensitive to wind conditions and effectively become very unsafe to operate in anything more than a brisk breeze. To put it lightly, even the average weather on the South Texas Gulf Coast is anything but conducive to the routine and reliable operation of giant cranes, which is exactly what SpaceX would need to avoid near-future Starship launch and recovery operations being constantly delayed by weather.
On January 9th, SpaceX appeared to test exactly that function. Before the day’s testing began, workers installed a large steel bar believed to be a weight simulator between the arms. Just like a booster would, the simulator sat – one end resting on both arms – on two small steel appendages identical to those present on all recent Super Heavy prototypes. On top of serving as a hardpoint for cranes, the downward-facing end of the L-shaped structures are capped with a small steel tip designed to take the whole weight of a Super Heavy. Those two minuscule steel caps – each no more than a foot wide – are what SpaceX (or at least CEO Elon Musk) wants Super Heavy to ‘land’ on to be “caught” by the launch tower’s arms.
More importantly, those caps – covering heavy-duty bearings – are also what the arms will ‘grab’ and manipulate to carefully position Super Heavy boosters for launch mount installation. To do so, each arm has a pair of parallel screw rods that can move together to shift the booster closer to or further away from the launch tower or move in opposite directions to slightly rotate it.
Once the arms reached the top of the tower, SpaceX performed several swing tests, mirroring the kind of movements they would use to carefully lift Starship, swing it over top of Super Heavy, and mate the two stages. Ultimately, the tower seemed to complete the simulation without any showstopping issues. Up next, it’s possible that SpaceX will add weights to the simulator bar to fully simulate the 100-200 ton masses of Starship and Super Heavy. Eventually, SpaceX may also use Starship S20 and Super Heavy B4 to fully qualify the arms by actually lifting, stacking, and removing both stages.
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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.
Tesla FSD v14.2.2 is getting rave reviews from drivers
Elon Musk’s Grok AI to be used in U.S. War Department’s bespoke AI platform
