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SpaceX rolls first Starship booster hardware to launch site
While destined to remain on the ground, SpaceX has rolled Starship booster hardware to its Boca Chica, Texas launch pad for the first time.
Back in March, SpaceX completed the process of stacking Super Heavy booster number 1 (BN1), creating what amounted to the largest rocket booster ever assembled. Plans and designs ultimately changed during that several-month process, leading SpaceX to write off the first completed Starship booster structure as a “pathfinder” and scrap it before it could complete a single test. As a result, BN1 never made it to SpaceX’s nearby launch and test facilities and was unceremoniously cut into pieces days later.
Ten weeks after that development, SpaceX is well into the process of stacking its first flightworthy Super Heavy booster (BN2 or BN3) and has officially delivered the first real booster hardware to the launch site for crucial qualification testing.
While only a ‘test tank,’ BN2.1’s arrival at SpaceX’s South Texas launch facilities is an undeniable sign that the company has finally settled on some sort of firm design for Starship’s first-stage booster – at least enough for a custom test article to be worth the time, effort, and money to build and test. BN2.1 is the eighth custom test tank built by SpaceX in the last ~18 months but it’s the first such test article to center around hardware specific to Super Heavy.
Technically, thanks to the fact that Starship and Super Heavy are built out of the exact same steel rings, baffles, and stringers with almost identical production hardware, all past test tanks – and even full Starships – simultaneously mature large portions of Starship’s booster.
Super Heavy requires several unique parts and sections, though. Unlike Starship, which is designed to ultimately have six Raptor engines installed, the ship’s booster will have anywhere from 29 to 32 Raptors and have to withstand almost five times the mechanical stress. That necessitates a drastically different thrust structure for Super Heavy, as well as all additional structural elements to support the 20 Raptor engines – compared to three on Starship – that will mount to the interior wall of its skirt rings.
Beyond Super Heavy’s thrust puck, the booster also requires a much larger transfer tube to feed far more liquid methane through its oxygen tank, a custom dome to connect to that transfer tube, and a custom forward dome and ring section to support four vast grid fins.
BN2.1 is never going to (intentionally) fly and is just a single test tank, which rules out installing actual engines. Now routine, SpaceX’s solution to that challenge of qualifying new hardware without risking catastrophic pad damage has involved building short ‘test tanks’ that are then filled with nonexplosive liquid nitrogen (LN2) and mechanically stressed with hydraulic rams instead of actual engines. Thus far, that process has seemingly been successful time and time again and has helped SpaceX qualify new steel alloys, thinner skin, new welding techniques, and new ‘thrust puck’ designs for Starship.
SpaceX has also tested early full-scale prototypes with the same hydraulic ram systems as a further hedge against quality assurance or fluke design issues that might not have been caught with test tanks. Whether or not BN2.1 is successful, it’s safe to assume that SpaceX will put its first flightworthy Super Heavy booster through a similar thrust puck stress test before attempting wet dress rehearsals or static fires.
Wasting no time at all, SpaceX has already scheduled road closures for what is likely BN2.1’s first round of tests no earlier than (NET) 12pm to 8pm CDT (17:00-03:00 UTC) on Monday, June 7th, with backup windows on the 8th and 9th. Stay tuned to find out if Super Heavy’s thrust puck survives its first nine-engine thrust puck shuck.
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
