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SpaceX has finally begun filling Starship’s orbital launch site fuel tanks
Almost five months after SpaceX began the process of filling and testing the first custom-built propellant storage system for Starship, the largest rocket ever built, the company has finally begun to fill the fuel half of the ‘tank farm’.
SpaceX began delivering truckloads of liquid nitrogen (LN2) to the LN2 and liquid oxygen (LOx) sections of the tank farm in mid-September 2021, well before the farm was anywhere close to completion. In about a month, SpaceX accepted ~60 LN2 deliveries – enough to partially fill one of the farm’s seven cryogenic tanks. Instead of some operational purpose, that LN2 was likely used to clean and partially proof the farm’s three LOx tanks. Just two weeks later, the orbital tank farm received its first LOx deliveries.
At the time, mere days after the basic structure of the main tank farm storage system was effectively completed, most figured that it would take SpaceX about as long to clean, proof, and begin filling the farm’s two liquid methane tanks. That would not be the case.
SpaceX installed the second of the farm’s two vertical SpaceX-built cryogenic liquid methane (LCH4) tanks in mid-October 2021. All seven cryogenic tanks had ‘sleeves’ – designed to be filled with foam insulation – installed by the end of the month, effectively completing the farm’s basic structure half a year after assembly began. However, around the same time, SpaceX also installed two horizontal tanks that were also identified as LCH4 storage – giving the overall tank farm far more fuel storage than its oxidizer (LOx) tanks could match. Starship’s Raptor engines burn about 3.55 kilograms of LOx for every 1 kilogram of LCH4.
As work on the vertical LCH4 tanks appeared to slow to a crawl, it took until December 2021 for SpaceX to begin cleaning and proofing the farm’s horizontal LCH4 tanks with liquid nitrogen. By that time, a rough unofficial narrative had been constructed to explain the lack of progress on the farm’s fuel half. Namely, in an excellent Twitter thread, CSI Starbase made a strong case that SpaceX appeared to have designed the first orbital-class Starship tank farm – a compact and pleasingly symmetric set of eight vertical storage tanks – without taking into consideration rudimentary Texas regulations for the storage of liquid natural gas and methane. By all appearances, that conclusion was correct, as the farm was visibly violating several rules – namely the requirements that all LCH4 storage be surrounded by six-foot-tall retaining walls and that all associated plumbing not be situated under power cabling.
As it exists, the LCH4 side of the vertical tank farm violates both of those rules and it’s not obvious that there is actually enough space between the two vertical methane tanks to build a retaining wall with two feet of horizontal clearance. It’s possible that the situation is more complex and that SpaceX intentionally broke those rules or was pursuing an exception to them but the end result was that those vertical LCH4 tanks have yet to be finished, let alone cleaned or proof tested. Instead, SpaceX appears to have fully refocused on horizontal tanks and most recently tore down a dirt berm beside them and began preparing foundations for at least two or three more.
Those horizontal tanks appear to store about 1000 cubic meters (~35,000 ft^3) of LCH4, while the vertical tanks would have stored about 1800 m^3. To fully replace them, SpaceX will need approximately four horizontal tanks – two more in addition to the two already installed. Thankfully, SpaceX has finally begun filling the already installed tanks while it works to expand the methane farm, beginning with three truckloads on the very first day – February 13th, 2022.

To fill the two existing tanks, which may store enough methane to fuel a stacked Starship and Super Heavy about 4/5ths of the way, SpaceX will need around 40-50 more tanker deliveries. Since last November, SpaceX has completed more than 320 liquid nitrogen and 200 liquid oxygen deliveries – equivalent to about 6700 tons (~14.8M lb) of LN2 and 4200 tons (~9.3M lb) of LOx. If SpaceX maintains that average and focuses entirely on LCH4, the two horizontal tanks could be filled to the brim before the end of February.
Having a substantial amount of LCH4 stored at the orbital tank farm will finally allow SpaceX to attempt the first major wet dress rehearsals (WDRs) and, more importantly, the first full static fires with flightworthy Super Heavy booster prototypes. Of course, a tank farm with full supplies of LOx, LCH4, LN2, and their gaseous equivalents is also a necessity for the first orbital Starship launch attempt, which has most recently slipped from a target of mid-2021 to no earlier than (NET) Q2 2022, pending regulatory approval.
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.