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SpaceX’s upgraded Super Heavy booster sails through first major test
SpaceX’s first upgraded 33-engine Super Heavy booster appears to have passed a crucial test with surprising ease, boding well for a smooth qualification process.
Attempting that test so early on did not appear to be SpaceX’s initial plan. Instead, shortly before Super Heavy Booster 4’s third and likely final removal from Starbase’s ‘orbital launch mount’ (OLM) on March 24th, SpaceX transported a massive structural test stand from a Starbase storage yard to the orbital launch site (OLS), where technicians have focused on modifying nearby ground systems to support apparent structural testing of Super Heavy Booster 7. As of March 31st, all available evidence suggested that SpaceX was preparing that stand to verify Booster 7’s mechanical strength and simulate the major stresses it might experience before investing a significant amount of time and resources in qualification testing.
However, SpaceX appeared to change its plans at the last minute.
Instead of starting with structural testing, after a brief two-day pause, SpaceX rolled Super Heavy B7 into place and craned the giant booster onto the orbital launch mount on April 2nd. On April 3rd, the launch mount’s “quick disconnect” device connected Super Heavy to the pad’s ground systems. On April 4th, just two days after its installation on the OLM, Super Heavy B7 kicked off the first in a series of qualification tests that will determine when or if the booster ultimately supports Starship’s first orbital launch attempt.
If testing goes perfectly, SpaceX CEO Elon Musk recently stated that Starship and Super Heavy – likely Ship 24 and Booster 7 – could be ready for an inaugural orbital launch attempt as early as May 2022. SpaceX appears to have leaped headfirst into Super Heavy Booster 7 qualification testing in a move that significantly increases the likelihood of meeting that extremely ambitious schedule. Normally, with a first-of-its-kind prototype debuting multiple significant design changes, SpaceX would start slow, possibly beginning with a basic pneumatic proof test to verify structural integrity at flight pressures – about 6.5-8.5 bar (95-125 psi) – with benign nitrogen gas before calling it a day.
With Booster 7, SpaceX likely still performed a quick pneumatic proof but then immediately proceeded into a full-scale cryogenic proof test. With Super Heavy B4, for example, SpaceX performed several increasingly ambitious cryogenic proof tests, filling the booster more and more each attempt but never actually topping it off. On Booster 7’s very first day of testing and first cryogenic proof attempt, SpaceX fully loaded the upgraded Super Heavy with a cryogenic fluid (likely liquid nitrogen) in just two hours – all with no significant unplanned holds (pauses).
In those two hours, SpaceX likely loaded Super Heavy B7’s liquid methane (LCH4) and oxygen (LOx) tanks with roughly 3400 metric tons (~7.5M lb) of liquid nitrogen (LN2) – not far off what Super Heavy would actually weigh at liftoff. At the peak of the test, Booster 7 was almost entirely covered in a thin layer of ice produced as the cryogenic liquid inside its tanks froze water vapor in the humid South Texas air onto its skin – an effect that effectively turns uninsulated cryogenic rockets into giant fill gauges. On top of running into no apparent issues, Super Heavy B7’s first cryogenic proof is also the first time any Super Heavy prototype has been fully filled during testing – an important milestone for any rocket prototype, let alone the largest rocket booster ever built.
Completing a full cryogenic proof test on its first try makes Booster 7 fairly unique among all Starship prototypes – not just Super Heavies. The contrast with Booster 4, which barely completed a handful of partial cryogenic proof tests in more than half a year spent at Starbase’s orbital launch site, is also extremely encouraging, suggesting that Booster 7 won’t be sitting inactive for months at a time.
Still, cryogenic proofing is just one of several important tests Booster 7 needs to complete. Even if the first test was nearly perfect and SpaceX doesn’t attempt one or several more cryoproofs with higher tank pressures or other tweaked variables, Super Heavy B7 needs to complete wet dress rehearsal testing (WDR) with flammable LCH4/LOx propellant and demonstrate autogenous pressurization (using heated propellant gas to pressure its tanks). At some point, SpaceX will also need to install a full 33 Raptor V2 engines on the booster and seal off the whole engine section and each Raptor with a heat shield.
Depending on how many Raptor V2 engines are available, SpaceX could begin static fire testing with just a few engines installed and shielded and then install the rest of the engines and heat shield later on. On the other hand, performing static fires without a full heat shield could risk damaging unprotected cabling or other subsystems, in which case wet dress rehearsal testing would likely follow immediately after cryoproofing and before engine or shield installation. After being skipped over, the structural test stand may also factor into Booster 7 qualification sometime before engine installation.
All told, plenty of uncertainty remains, but Super Heavy B7’s auspicious start suggests that the Booster 4 experience is far from a template and that SpaceX is much less interested in wasting time this time around.
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.
Elon Musk
Judge clears path for Elon Musk’s OpenAI lawsuit to go before a jury
The decision maintains Musk’s claims that OpenAI’s shift toward a for-profit structure violated early assurances made to him as a co-founder.
A U.S. judge has ruled that Elon Musk’s lawsuit accusing OpenAI of abandoning its founding nonprofit mission can proceed to a jury trial.
The decision maintains Musk’s claims that OpenAI’s shift toward a for-profit structure violated early assurances made to him as a co-founder. These claims are directly opposed by OpenAI.
Judge says disputed facts warrant a trial
At a hearing in Oakland, U.S. District Judge Yvonne Gonzalez Rogers stated that there was “plenty of evidence” suggesting that OpenAI leaders had promised that the organization’s original nonprofit structure would be maintained. She ruled that those disputed facts should be evaluated by a jury at a trial in March rather than decided by the court at this stage, as noted in a Reuters report.
Musk helped co-found OpenAI in 2015 but left the organization in 2018. In his lawsuit, he argued that he contributed roughly $38 million, or about 60% of OpenAI’s early funding, based on assurances that the company would remain a nonprofit dedicated to the public benefit. He is seeking unspecified monetary damages tied to what he describes as “ill-gotten gains.”
OpenAI, however, has repeatedly rejected Musk’s allegations. The company has stated that Musk’s claims were baseless and part of a pattern of harassment.
Rivalries and Microsoft ties
The case unfolds against the backdrop of intensifying competition in generative artificial intelligence. Musk now runs xAI, whose Grok chatbot competes directly with OpenAI’s flagship ChatGPT. OpenAI has argued that Musk is a frustrated commercial rival who is simply attempting to slow down a market leader.
The lawsuit also names Microsoft as a defendant, citing its multibillion-dollar partnerships with OpenAI. Microsoft has urged the court to dismiss the claims against it, arguing there is no evidence it aided or abetted any alleged misconduct. Lawyers for OpenAI have also pushed for the case to be thrown out, claiming that Musk failed to show sufficient factual basis for claims such as fraud and breach of contract.
Judge Gonzalez Rogers, however, declined to end the case at this stage, noting that a jury would also need to consider whether Musk filed the lawsuit within the applicable statute of limitations. Still, the dispute between Elon Musk and OpenAI is now headed for a high-profile jury trial in the coming months.
Tesla’s Elon Musk: 10 billion miles needed for safe Unsupervised FSD
Tesla earns top honors at MotorTrend’s SDV Innovator Awards
