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High winds scrub SpaceX Starship SN9’s Monday launch attempt
Update (2:30 pm CST): SpaceX appears to have called off Monday’s Starship SN9 launch attempt due (primarily) to high winds along the flight corridor. Additional opportunities are available from 8 am to 6 pm CST (UTC-6) on Tuesday (Jan 26) and Wednesday (Jan 27).
Technically, lacking any official confirmation, there’s still a chance of a launch attempt or additional ground testing happening today but either possibility is extremely unlikely at this point.
Update: SpaceX has completed what is known as a Flight Readiness Review (FRR) and determined that Starship prototype SN9 is ready to attempt its first high-altitude launch as early as today.
All necessary aviation and maritime notices and restrictions are in place and the company has begun the process of closing a public highway and clearing the launch site of employees. Today’s (Jan 25) launch window lasts from noon to 6 pm CST (UTC-6) and Starship SN9 could likely be made ready to launch anytime after 2pm be ready to fly as early as 4 pm CST according to a loudspeaker announcement at the launch pad. Stay tuned for updates and, hopefully, an official SpaceX webcast.
All signs point to SpaceX’s second high-altitude Starship prototype preparing for a 12.5-kilometer (~40,000 ft) as early as Monday, January 25th in a bid to rectify a last-second bug that caused its predecessor to explode last month.
Known as Starship serial number 8 (SN8), the SpaceX-built prototype was the first to have its basic airframe (tank and nose sections) fully integrated, as well as the first Starship to attempt to break the 150m (~500 ft) ceiling set by Starhopper, SN5, and SN6. Break the ceiling SN8 most certainly did, performing a spectacularly successful 12.5 km launch that aced almost every single goal SpaceX had hoped to complete. Keyword almost.
After an impressive 280 seconds of uninterrupted operation of its Raptors, Starship SN8 shut down the last of those three engines, flipped onto its belly, and successful freefell ~12 kilometers back to Earth. The rocket then carried that success even further, reigniting two Raptors, performing a dramatic 120-degree flip, orienting itself vertically, and beginning to slow down for a soft landing.
Only then did Starship SN8’s performance deviate from virtual perfection. At T+6:38, a few seconds after beginning its crucial landing burn, one of Starship’s active Raptors shut down and the other effectively stopped generating thrust. The reason, CEO Elon Musk would later explain, was low head pressure in a smaller tank (‘header tank’) dedicated to supplying fuel during Starship’s wild flip and landing maneuver. It was never confirmed if the Raptor engine shutdown observed milliseconds prior to the other engine losing thrust was intentional.
Cause aside, the end result was unsurprising: without enough thrust to slow down, Starship SN8 accurately impacted the concrete landing zone but did so at high speed – likely around 50-60 m/s (100-150 mph). Given that Starhopper and Starships SN5 and SN6 had already successfully proven Starship’s ability to gently land from 150 meters on a single Raptor engine and that, prior to SN8, Starship’s bizarre belly-flop descent and 90-degree flip had been almost entirely theoretical, SpaceX deemed the launch a spectacular success.
Nothing better exemplifies that than the fact that a little over a month later, SpaceX quite literally began scrapping the most complex, completed section of a future Starship prototype (SN12) before it ever reached the assembly phase. Instead, SpaceX appears to be more focused than ever on a mysterious series of “major” upgrades Musk has said will debut on Starship SN15. Nearly all SN15 subsections have been completed and are simply waiting to be joined together, while parts of SN16 and SN17 are also starting to pile up in staging areas.
Starship SN10 is practically ready to move to the launch pad to prepare for flight as soon as SpaceX chooses to do so and Starship SN11 is likely no more than a week or two of work away from reaching same level of readiness.
Ultimately, despite a long and delay-ridden test campaign, Starship SN9 finally completed what looked like a full-duration static fire of all three of its Raptor engines – the rocket’s sixth static fire overall. On Saturday, January 23rd, SpaceXers installed SN9’s flight termination system (FTS) – a system of explosives designed to destroy Starship if it flies too far off course. For Starship, FTS installation all but guarantees that a launch attempt is a matter of days away. Fresh county roadblocks, Temporary Flight Restrictions (TFRs) granted by the FAA, and Coast Guard a safety notice further imply that SN9 will attempt to launch as early as Monday morning, January 25th, with backup opportunities on Tuesday and Wednesday.
With any luck, like SN8’s high-altitude debut, SpaceX hopefully livestream Starship SN9’s own attempt at the same feat. Stay tuned for more details as they come.
Tesla’s Head of AI, Ashok Elluswamy, says that something that was expected with version 14.3 of the company’s Full Self-Driving platform has already partially shipped with the current build of version 14.2.
Tesla and CEO Elon Musk have teased on several occasions that reasoning will be a big piece of future Full Self-Driving builds, helping bring forth the “sentient” narrative that the company has pushed for these more advanced FSD versions.
Back in October on the Q3 Earnings Call, Musk said:
“With reasoning, it’s literally going to think about which parking spot to pick. It’ll drop you off at the entrance of the store, then go find a parking spot. It’s going to spot empty spots much better than a human. It’s going to use reasoning to solve things.”
Musk said in the same month:
“By v14.3, your car will feel like it is sentient.”
Amazingly, Tesla Full Self-Driving v14.2.2.2, which is the most recent iteration released, is very close to this sentient feeling. However, there are more things that need to be improved, and logic appears to be in the future plans to help with decision-making in general, alongside other refinements and features.
On Thursday evening, Elluswamy revealed that some of the reasoning features have already been rolled out, confirming that it has been added to navigation route changes during construction, as well as with parking options.
He added that “more and more reasoning will ship in Q1.”
🚨 Tesla’s Ashok Elluswamy reveals Nav decisions when encountering construction and parking options contain “some elements of reasoning”
More uses of reasoning will be shipped later this quarter, a big tidbit of info as we wait v14.3 https://t.co/jty8llgsKM
— TESLARATI (@Teslarati) January 9, 2026
Interestingly, parking improvements were hinted at being added in the initial rollout of v14.2 several months ago. These had not rolled out to vehicles quite yet, as they were listed under the future improvements portion of the release notes, but it appears things have already started to make their way to cars in a limited fashion.
Tesla Full Self-Driving v14.2 – Full Review, the Good and the Bad
As reasoning is more involved in more of the Full Self-Driving suite, it is likely we will see cars make better decisions in terms of routing and navigation, which is a big complaint of many owners (including me).
Additionally, the operation as a whole should be smoother and more comfortable to owners, which is hard to believe considering how good it is already. Nevertheless, there are absolutely improvements that need to be made before Tesla can introduce completely unsupervised FSD.
Elon Musk
Tesla’s Elon Musk: 10 billion miles needed for safe Unsupervised FSD
As per the CEO, roughly 10 billion miles of training data are required due to reality’s “super long tail of complexity.”
Tesla CEO Elon Musk has provided an updated estimate for the training data needed to achieve truly safe unsupervised Full Self-Driving (FSD).
As per the CEO, roughly 10 billion miles of training data are required due to reality’s “super long tail of complexity.”
10 billion miles of training data
Musk comment came as a reply to Apple and Rivian alum Paul Beisel, who posted an analysis on X about the gap between tech demonstrations and real-world products. In his post, Beisel highlighted Tesla’s data-driven lead in autonomy, and he also argued that it would not be easy for rivals to become a legitimate competitor to FSD quickly.
“The notion that someone can ‘catch up’ to this problem primarily through simulation and limited on-road exposure strikes me as deeply naive. This is not a demo problem. It is a scale, data, and iteration problem— and Tesla is already far, far down that road while others are just getting started,” Beisel wrote.
Musk responded to Beisel’s post, stating that “Roughly 10 billion miles of training data is needed to achieve safe unsupervised self-driving. Reality has a super long tail of complexity.” This is quite interesting considering that in his Master Plan Part Deux, Elon Musk estimated that worldwide regulatory approval for autonomous driving would require around 6 billion miles.
FSD’s total training miles
As 2025 came to a close, Tesla community members observed that FSD was already nearing 7 billion miles driven, with over 2.5 billion miles being from inner city roads. The 7-billion-mile mark was passed just a few days later. This suggests that Tesla is likely the company today with the most training data for its autonomous driving program.
The difficulties of achieving autonomy were referenced by Elon Musk recently, when he commented on Nvidia’s Alpamayo program. As per Musk, “they will find that it’s easy to get to 99% and then super hard to solve the long tail of the distribution.” These sentiments were echoed by Tesla VP for AI software Ashok Elluswamy, who also noted on X that “the long tail is sooo long, that most people can’t grasp it.”
News
Tesla earns top honors at MotorTrend’s SDV Innovator Awards
MotorTrend’s SDV Awards were presented during CES 2026 in Las Vegas.
Tesla emerged as one of the most recognized automakers at MotorTrend’s 2026 Software-Defined Vehicle (SDV) Innovator Awards.
As could be seen in a press release from the publication, two key Tesla employees were honored for their work on AI, autonomy, and vehicle software. MotorTrend’s SDV Awards were presented during CES 2026 in Las Vegas.
Tesla leaders and engineers recognized
The fourth annual SDV Innovator Awards celebrate pioneers and experts who are pushing the automotive industry deeper into software-driven development. Among the most notable honorees for this year was Ashok Elluswamy, Tesla’s Vice President of AI Software, who received a Pioneer Award for his role in advancing artificial intelligence and autonomy across the company’s vehicle lineup.
Tesla also secured recognition in the Expert category, with Lawson Fulton, a staff Autopilot machine learning engineer, honored for his contributions to Tesla’s driver-assistance and autonomous systems.
Tesla’s software-first strategy
While automakers like General Motors, Ford, and Rivian also received recognition, Tesla’s multiple awards stood out given the company’s outsized role in popularizing software-defined vehicles over the past decade. From frequent OTA updates to its data-driven approach to autonomy, Tesla has consistently treated vehicles as evolving software platforms rather than static products.
This has made Tesla’s vehicles very unique in their respective sectors, as they are arguably the only cars that objectively get better over time. This is especially true for vehicles that are loaded with the company’s Full Self-Driving system, which are getting progressively more intelligent and autonomous over time. The majority of Tesla’s updates to its vehicles are free as well, which is very much appreciated by customers worldwide.
Tesla AI Head says future FSD feature has already partially shipped
Tesla’s Elon Musk: 10 billion miles needed for safe Unsupervised FSD
