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SpaceX to put custom Starship propellant storage tanks through first trial
In the latest twist in the saga of SpaceX’s custom-built Starship launch pad propellant storage tanks, the company appears to have retroactively decided to build small prototype meant solely for testing.
Known as a ‘test tank,’ the relatively small steel structure was fairly rapidly assembled from parts of an older Ground Support Equipment (GSE) tank scrapped in July over the last week or so. SpaceX completed the first Starship-derived propellant storage tank in April 2021 and rapidly rolled that tank (GSE1) and a second (GSE2) from the build site to the orbital launch pad just a few weeks apart. Less than a month after that, SpaceX also completed GSE tank #3, though things seemingly devolved into chaos immediately thereafter.
Only three months later would GSE3 finally be transported to – and installed on a concrete mount at – Starship’s first orbital launch site, and only after a number of structural modifications and in the footsteps of GSE tanks #5 and #6. Little is known about why SpaceX’s custom GSE tank production faltered so soon after it began, why none of the five Starship-sized tanks installed at the orbital pad have been fully plumbed or subjected to any kind of testing, or why structural modifications were seemingly required after the fact. However, it’s safe to say that SpaceX’s brand new GSE ‘test tank’ is now at the center of the mystery.
Thankfully, at minimum, the rapid appearance of SpaceX’s first GSE test tank returns some level of familiarity to the brief but chaotic history of Starship’s orbital launch pad propellant tanks. Test tanks are nothing new and have been an integral part of Starship development since Test Tank 1 first headed to SpaceX’s suborbital launch (and test) facilities in January 2020. In the 20 months since, SpaceX has built and tested seven small test tanks, several of which didn’t survive.
Whether intentionally destroyed or not, each test tank explicitly helped SpaceX qualify new manufacturing techniques, different materials, and different skin thickness and generally gather data more quickly and cheaply than full-scale prototypes would allow. Most recently, for example, SpaceX seemingly successfully tested a Super Heavy booster test tank, subjecting the prototype to cryogenic liquid nitrogen and using hydraulic rams to simulate the thrust of nine Raptor engines on an unproven disk-like thrust structure.
Now, almost as if SpaceX snapped out of a trance and remembered the utility of test tanks, the company has assembled a subscale GSE prototype presumably meant to verify that its custom-built propellant storage tanks can handle a set of conditions significantly different from the Starships they’re derived from. In this case, that GSE tank was quite literally built from scrapped sections of GSE tank #4. In fact, the top half (forward dome section) was quite literally cut off of GSE4 after the tank was scrapped last month for unknown reasons.
Over the last several months, while GSE tank production and installation took an unexpected hiatus, SpaceX workers slowly but surely welded steel rings (stiffeners) to the exterior of GSE1, GSE2, and GSE3. When GSE5 and GSE6 eventually headed to the pad, they left with those stiffeners already installed, implying that whatever tripped SpaceX up was likely structural. The GSE4 test tank also includes external stiffeners along each circumferential weld (where rings were stacked or domes joined).
At the same time as SpaceX was (or wasn’t, for several months) building its own GSE tanks, contractors normally tasked with assembling water towers and storage tanks in situ built eight massive 12m (~40 ft) wide tanks of their own. Deemed “cryo shells,” much like their name suggests, those tanks are meant to fully enclose SpaceX’s GSE tanks. SpaceX will use those shells to insulate their thin, single-walled steel propellant tanks, thus keeping their cryogenic contents cryogenic for as long as possible. How they’ll be insulated is unclear, though.
Based on the seemingly retroactive decision to strengthen the exterior of those GSE tanks, the general consensus as of late is that SpaceX wants to pull at least a partial vacuum in the gap between shell and tank. It’s also possible that SpaceX will do the opposite and pressurize that gap (as much as possible) with an insulative gas like nitrogen. Extra confusion comes from the fact that Starship tanks are technically designed to support a literal spacecraft (operating in a near-total vacuum) without the need for external stiffeners.
Additionally, it’s fairly clear that SpaceX hasn’t built a custom subscale cryoshell or concrete installation pad for its GSE4 test tank, meaning that it will really only be useful for testing some of the loads operational GSE tanks will experience inside their sleeves. Additionally, given that SpaceX has already completed six of the orbital pad’s seven GSE tanks and all seven of their cryosleeves, the discovery of any significant issues during GSE4 testing could easily trigger months of rework and delays. With any luck, though, GSE4 will sail through an imminent test campaign, clearing the way for SpaceX to finish plumbing, sleeving, and activating Starship’s first orbital launch site tank farm.
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
