News
SpaceX to attempt to crush Starship test tank
A week after rolling a different ‘test tank’ from its South Texas Starship factory to nearby launch and test facilities, SpaceX has moved a second test tank to the pad.
Hearkening back to a period in 2020 where SpaceX built and tested six different Starship test tanks in a period of six months, the company appears to be preparing to test another batch of tanks in the hopes of qualifying Super Heavy booster design changes and clearing the way for a significant upgrade to all Starship tank domes. The sequencing of the latest tank raises some questions, however.
Known unofficially as the “EDOME” tank in reference to a cryptic label on the side of one of its halves, the first new test tank’s purpose is much more cut and dry. While its steel rings appear to be unchanged from current Starship and Super Heavy prototypes, the tank’s two domes share almost nothing in common with the dozens of domes SpaceX has built and tested over the last three years of development. The new domes are much simpler and should be easier to manufacture than the domes SpaceX is familiar with. Thanks to their more spherical shape, they should also be more efficient, allowing future Starship tanks to store a bit more propellant while taking up the same amount of vertical space. SpaceX has yet to begin testing the EDOME tank since its June 8th rollout and does not appear to be much closer to starting 12 days later.
On June 16th, SpaceX rolled a second test tank to the launch site, which eventually joined the EDOME tank at a staging area that used to be a Starship landing pad. Whereas the EDOME tank is more of a generic test article, the second tank – known as B7.1 – is specifically designed to test Super Heavy booster design changes.
B7.1 is a bit like a miniature Super Heavy. Its three-ring top section is mostly similar to the top section of a booster and is reinforced with dozens of external stringers. Oddly, it is missing cutouts for grid fins, and the tank’s forward dome does not have the reaction frame those hypothetical grid fins would anchor to. On the tank’s bottom half, the same stringers are present, and the tank features a new design that squeezes four slightly shorter rings into the same height as three. The Super Heavy thrust dome those rings enclose is also a new design that expands the number of central Raptor engines from 9 to 13.
It’s unsurprising that SpaceX wants to test those significant design changes. SpaceX did technically conduct a similar test in mid-2021 with a test tank known as BN2.1, but that tank featured a thrust dome with room for 9 older Raptors that would have generated about ~1700 tons of thrust. B7.1’s testing will go a step further than BN2.1 and use a structural test stand that should allow SpaceX to simulate the compressive forces Super Heavy boosters might experience in flight, adding another dimension of stress on top of the 13 hydraulic rams that will simultaneously subject the test tank to the equivalent of ~3000 tons (~6.6M lbf) of thrust.
And lift over to the crusher for a nice bit of torture. pic.twitter.com/SxV3BTs7ry— Chris Bergin – NSF (@NASASpaceflight) June 19, 2022
What is surprising, however, is the fact that SpaceX has waited so long to build and test a tank like B7.1. SpaceX has already completed an entire Super Heavy booster (B7) with all the design changes B7.1 is meant will test and recently installed 33 new Raptor 2 engines on that prototype. A second upgraded booster, B8, is also nearly finished. In that sense, B7.1 is quite unusual and feels more like a reluctant afterthought than part of a methodical development process. If B7.1 suffers an unintentional failure during testing, SpaceX could be forced to abandon two nearly-finished Super Heavy boosters, wasting months of assembly and testing and rendering prototypes that are likely worth tens of millions of dollars all but useless.
The design changes B7.1 is meant to test are not exactly radical, but it’s still unclear why SpaceX has chosen to conduct those tests after building two entire Super Heavy boosters. Earlier on in Starship development, SpaceX regularly used test tanks to qualify significant design changes before applying those changes to full prototypes, limiting the amount of resources that could be wasted on any unproven prototype. Thankfully, Super Heavy Booster 7 may have already completed similar Raptor thrust simulation tests on the same test stand B7.1 was recently installed on, meaning that SpaceX’s confidence may have been well-placed. However, if the first use of the ‘can crusher’ stand on a Super Heavy test tank finds any problems or ends in failure, B7 and B8 could still be easily rendered unusable or incapable of flight, significantly delaying Starship’s first orbital launch attempt.
Lately, SpaceX has been focused on preparing Starship S24 and Super Heavy B7 for static fire tests that could eventually qualify the pair to support the first orbital test flight. It’s not clear if or when SpaceX will be able to set aside time and evacuate Starbase’s busy orbital launch site to test B7.1 or the EDOME tank.
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.
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
