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SpaceX upgrading Starship noses and domes for easier assembly
While a separate team closes in on the completion of a new and improved Starship nosecone, SpaceX also appears to have begun assembling upgraded ‘tank domes’ that feature a similar underlying design change.
On the nose front, SpaceX has been working on a new and improved version of Starship’s nosecone for at least a year and assembling pathfinders and prototypes of varying fidelity since mid-2020 – around the same time when Starship SN15 became the first (and only) prototype to successfully launch and land. Further down the rocket, hints of Starship dome upgrades are a much more recent development.
Excluding Starship Mk1, which never had its far flimsier nose fully installed, the Starship nose design has been extremely consistent ever since SpaceX began building the first prototypes in mid-2020. Early prototypes were inevitably scrapped as SpaceX quickly iterated on the nose design and assembly process, culminating in Starship SN8, which became the first prototype to have its basic structure (tank section, nose, and flaps) fully assembled.
Though improvements and changes have almost certainly been made in the last ~18 months, the early unflown prototypes and the noses of Starships SN8, SN9, SN10, SN11, SN15, SN16, S20, and S22 have all been constructed in roughly the same way. SpaceX would first produce a series of thin, stamped sheets (gores) of steel. Once aligned on custom-built jigs, each of those gores would be welded together to form a slightly conical ring. Five total ‘rings’ would be assembled, each narrower and more conical than the last. The five sections would then be stacked one by one and welded together along their circumferences.
Altogether, something like 120 complex vertical welds would be needed just to assemble the most basic structure of a nose, followed by four or five no less complex circumferential welds to turn those sections into one cone. SpaceX’s upgraded design seeks to simplify that process mainly by increasing the size of the gores. Aside from modestly reducing the number of longitudinal sections needed to form the cone, SpaceX has also reduced the number of stacked sections from five to two, slashing the total number of gores needed by at least a factor of two or three. While not quite as substantial, the same simplification also reduces the length of vertical and circumferential welds needed to assemble a nosecone.
The spirit behind SpaceX’s new dome design appears to be very similar. Presumably doubling down on the stretch-forming production method developed for nosecone gores, SpaceX appears to have also decided to increase the size of dome gores and reduce the number of stacked sections required for dome assembly – albeit from three to two instead of five to two.
Collectively, this behavior is mostly predictable. With increasing confidence in the current design of Starship and Super Heavy, SpaceX now appears to be looking for ways to streamline and simplify manufacturing while simultaneously optimizing Starship’s design. Regardless of whether one is dealing with a highly advanced rocket factory or a smartphone assembly line, part count reduction is a very common and desirable way to reduce both cost and complexity. Additionally, drastically reducing the number of individual welds – and, to a slightly lesser degree, the total length of welds – required should also reduce the number of possible points of failure and the time needed for weld inspection and repair.
Having already scrapped a number of new nose pathfinders, it appears that Starship S24 will be the first to feature the new design. The process of stacking the ship has already begun. For domes, SpaceX appears to have only just begun assembling the first prototypes. If past dome changes are indicative of future behavior, one or several new ‘test tanks’ will likely be built to ensure that the new dome design performs as well as present-day hardware. It’s also unclear if SpaceX aims to replace all domes with a more spherical design or if, say, current Starship and Super Heavy thrust domes will remain the same for the time being.
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
