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SpaceX set to finish three Starship prototypes in the same month
SpaceX appears to be on track to complete its third Starship prototype in a month just days after the company finished testing a new steel tank and at the same time as it prepares to roll another full-scale ship to the launch pad.
Postponed by several weeks after the (fleeting) success of the Starship serial number 4 (SN4) prototype, violently destroyed by a minor testing mishap on May 29th, SpaceX’s fifth full-scale Starship tank section (SN5) could roll to an adjacent testing facility at any point in the next few days. In fact, SN4’s successor has likely been ready to begin tank proof and static fire testing for several weeks since it was stacked to its full height on May 12th. SN4 rolled to the launch pad on April 23rd and remained SpaceX’s top Starship priority until its demise more than a month later.
As it turns out, the explosion that destroyed the ship also launched a ~25 metric ton (~55,000 lb) counterweight installed a few days prior some 100m (300+ ft) into the air, where it proceeded to fall back to earth and obliterate the steel mount Starship SN4 sat on. The loss of that pad hardware necessitated its own several-week delay but SpaceX appears to be nearly done installing and outfitting replacements as of June 18th – an incredible turnaround given the scale and complexity of everything involved. Of course, the whole purpose of those rapid repairs is to get back to the business of testing Starships as quickly as possible.
SN5
Initially expected as early as 8am local on June 17th, Starship SN5’s trip to the launch pad has been a long time coming. Completed around May 20th after approximately a month of concerted effort, the ~30m (100 ft) tall tank departed SpaceX’s Vehicle Assembly Building (VAB) for the first on June 13th, although it was quickly moved back inside as technicians simultaneously worked to complete Starship SN6.
Previously scheduled to become the first Starship to reach its full height with the installation of a functional nosecone, SN5 will likely pick up where SN4 left off, instead. That process will effectively be no different, albeit sans nosecone, starting with ambient and cryogenic proof (pressure) tests and eventually moving to one or several static fires with either one or three Raptor engines. Testing the quick disconnect umbilical port that caused SN4’s demise will also likely be a priority. If all goes according to plan in that first week or two of tests, SpaceX may finally be ready to launch a full-scale Starship prototype for the first time, performing a 150m (~500 ft) hop test with SN5.
However, since CEO Elon Musk first discussed plans for an initial 150m hop test, SpaceX received a surprise suborbital launch license from the FAA, rather than the limited experimental permit most expected. That license effectively allows SpaceX to perform an unlimited number of Starship tests as long as the trajectory follows the administration’s strict safety guidelines and remains suborbital. Unless SpaceX’s ~150m target was based in some technical limitation, the sky is quite literally the limit for a more ambitious flight debut if the company believes Starship SN5 can handle it.
SN6
In the event that Starship SN5 follows its predecessor into a less early (but still early) grave, SpaceX thankfully won’t have to wait long at all to continue its hardware-rich test program. When Starship SN5 first departed the VAB on June 13th, it did so to give SpaceX room to finish Starship SN6, placing its aft engine section on a stand inside the building and stacking the upper two-thirds of the ship’s tank on top.
Several days to a week or more of internal and external work remain to fully mate the two Starship SN6 sections, but the vast majority of its assembly is now behind SpaceX. SpaceX continues to refine its methods with each successive prototype, gradually producing Starships that are getting closer and closer to the ideal finished product. There’s a chance that, unlike Starship SN4, SN5 can be modified with the installation of a nosecone and flaps to support more ambitious 2-20 km (~1.2-12 mi) flight tests if it makes it over the 150m hurdle unscathed but if not, SN6 could become the first Starship to have a nosecone installed.
SN7
Last but absolutely not least, SpaceX recently built a new Starship test tank for the first time since March. While stouter than an actual Starship-class methane or oxygen tank, this particular test tank is maybe only 25% shorter than the methane tanks installed on Starship prototypes. According to Musk and effectively confirmed by writing all over the prototype, this particular test tank – formerly Starship SN7 – was built to determine if a different kind of steel could be preferable for future ships.
Shortly after the June 15th test began to wind down, Musk announced that the new material (304L stainless steel) had performed quite well, reaching 7.6 bar (110 psi) before it sprung a leak. The fact alone that it sprung a leak instead of violently depressurizing is already a major sign that 304L is preferable to 301L, as it means that Starships built out of it could fail much more gracefully in the event of a leak instead of collapsing or violently exploding. A step further, SpaceX has already managed to repair the leak on SN7 and will likely test the tank again in the next few days.
Meanwhile, Musk says that a second improved 304L test tank is already on its way, after which SpaceX will likely attempt to build and test the first fully-304L Starship prototype. Further down the line, SpaceX intends to develop its own custom steel alloy, optimized specifically for Starship’s needs. The first tests of that ’30X’ alloy could begin as early as August 2020 according to a February Musk tweet.
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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
