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SpaceX CEO Elon Musk reveals photos of Starship’s first completed Raptor engine
Shortly after Teslarati reported that the first operationalized Raptor had shipped to McGregor, Texas for its first full-scale static fire tests, SpaceX CEO Elon Musk took to Twitter to post the first official photos of the “radically redesigned” engine preparing for its critical debut test fire in Texas.
Designed with extreme reliability, efficiency, and reusability in mind, the Raptor seen in Musk’s photos is rated for just shy of 2.5 times the thrust of Merlin 1D at 200 tons (450,000 lbf) and has been commonized across both stages of BFR (Starship and Super Heavy) to spread out development costs and speed up the next-generation rocket’s orbital launch debut.
Preparing to fire the Starship Raptor engine at @SpaceX Texas pic.twitter.com/8JCOi1BG6z
— Elon Musk (@elonmusk) February 1, 2019
Aside from revealing some impressive photos of the first upgraded Raptor preparing for a static fire test, Musk went into a bit more detail on the future of the engine and its probable development path, describing Raptor in its current iteration as a sort of compromise between achieving nominal performance and minimizing the cost and timescale to arrive at a flight-ready engine. Currently stationed at SpaceX’s McGregor, Texas development and testing facilities, Raptor appears to feature an expansion ratio somewhere in between Merlin 1D (optimized for sea-level) and MVac (optimized for vacuum).
Initially making one 200 metric ton thrust engine common across ship & booster to reach the moon as fast as possible. Next versions will split to vacuum-optimized (380+ sec Isp) & sea-level thrust optimized (~250 ton).
— Elon Musk (@elonmusk) February 1, 2019
This increases the stress on the nozzle during ignition and operation at normal atmospheric pressures but it also improves engine efficiency once Starship (or Super Heavy) rises above the thickest parts of Earth’s atmosphere, even if a medium-expansion nozzle still can’t touch the performance of a giant vacuum-optimized bell like those used by MVac. As such, BFR in its earliest iterations will be significantly less capable than a fully-optimized version of the rocket when it comes to high-energy Earth/lunar orbits and interplanetary trajectories, a challenge that can at least initially be hurdled by accepting much lower nominal payload capabilities and relying on brute-force performance, much like Falcon 9 and Heavy.

Assuming the first hot-fire tests of the full-scale, operationalized Raptors go well, three of the next-gen engines could support the first hop tests of a full-scale Starship prototype sometime in the next few months, potentially as early as late-February or March. Musk also reiterated that Starship’s complimentary booster – known as Super Heavy and set to begin initial prototype assembly as early as April – will feature 31 Raptor engines capable of producing upwards of 12.4 million pounds of thrust (62,000 kN) at liftoff. However, Musk indicated that the sheer value of 31 advanced Raptor engines also means that the first Super Heavy flights may only feature a partial complement of engines in case the vast booster experiences a failure, far from uncommon during the first few launches of a new rocket.
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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.