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SpaceX rolls upgraded Super Heavy booster to the launch pad
SpaceX has begun transporting an upgraded Super Heavy booster to its South Texas launch facilities, where the rocket will likely be tested with a rarely used stand known as the ‘can crusher’.
On Wednesday, March 30th, SpaceX scheduled a temporary road closure – indicative of transport operations – on March 31st. The Friday prior, Super Heavy Booster 7 (B7) left the high bay it was assembled in multiple times, only to roll back inside at the end of the day. More likely than not, SpaceX decided to keep working on the booster inside the shelter of the high bay while a different team focused on preparing Starbase’s orbital launch site (OLS) for B7’s arrival. Simultaneously, moving Booster 7 also made room for SpaceX to begin stacking Booster 8, which began the same day.
Work at the pad has centered around one thing in particular: a massive mechanical device affectionately known as the ‘can crusher.’ Made up of two large steel structures, that structural test stand’s primary purpose is, to some degree, to attempt to crush Starship test tanks and Super Heavy prototypes. SpaceX transported the bottom half of the structural test stand to the orbital launch site a few days before Booster 7’s first brief trip outside the high bay.
A few days later, pictured in the tweet above, unofficial aerial photography of Starbase revealed that SpaceX has modified the stand with 13 hydraulic rams, all but guaranteeing that it will be used to test SpaceX’s next Super Heavy. B7 is the first booster designed to use upgraded Raptor V2 engines – and 33 of them, no less. Boosters 3 and 4 had room for 29 older Raptors. That ~14% increase in engine count required a redesigned thrust section, raising the number of central gimballing Raptors from 9 to 13.
Raptor V2’s upgrades are far more consequential, however. On top of major design simplifications that should slash the cost of manufacturing, Raptor V2’s maximum thrust was boosted from about 185 tons to 230+ tons (~410,000-510,000 lbf). Combined with more engines, Super Heavy Booster 7 could theoretically produce around 7600 tons (~16.7M lbf) of thrust at liftoff, while Booster 4 – which never fired even one of its 29 Raptor V1.5 engines – could have produced about 5400 tons (~11.9M lbf). That 40% increase in max thrust likely necessitated a similarly strengthened thrust section, involving a large number of mostly invisible design changes.
Those changes now need to be qualified and it appears that SpaceX may use B7 – an entire Super Heavy booster that could one day fly – to verify their performance instead of a cheaper, more disposable test tank. The first part of that testing will likely involve simulating the thrust of at least 13 of Booster 7’s engines. The test stand’s ‘cap’ could also be installed on top of Booster 7 once it arrives at the pad, possibly allowing SpaceX to simulate both the thrust of all 33 engines and the stress caused by acceleration during launch, reentry, and landing. Finally, SpaceX has begun installing a custom fixture and plumbing that will allow all of that structural testing to occur while Super Heavy is loaded with liquid nitrogen (LN2) or oxygen (LOx), adding another layer of stress.
Assuming the structural test stand is strong enough to support a several-thousand-ton booster, SpaceX could also feasibly complete cryogenic proof tests (with benign LN2 or LOx) and even wet dress rehearsals (with flammable LOx and methane propellant) with the same setup. Fully proofed, Booster 7 could then be fitted with Raptor 2 engines and installed on Starbase’s ‘orbital launch mount’ for static fire testing.
Based on road closures, SpaceX at least wants the option to begin testing Booster 7 as early as Friday, April 1st – the day after it arrives at the launch site. If test readiness slips further to the right, which is likely, additional opportunities are available on April 4th and 5th.
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.”
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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
