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SpaceX rolls last Starship off the assembly line ahead of “major upgrades”
SpaceX has installed Starship serial number 11’s (SN11) steel nosecone, effectively completing the rocket and marking the end of production for a series of four virtually identical prototypes.
SpaceX has soared through a limited production run of four full-height Starship prototypes with a more or less frozen design, simultaneously serving as a pilot run for a nascent Starship assembly line while also producing high-fidelity prototypes for the program’s first high-altitude flight testing. Work on Starship SN8 – the first of those four prototypes – began around July 2020 when labeled hardware was first spotted.
Parts of SN9, SN10, SN11, and SN12 gradually started to appear over the next few months. Less than four months after production began, (half of) Starship SN8 rolled to the launch pad in late October to kick off a series of acceptance tests.
After an unusually long ~6 weeks of testing, SpaceX declared Starship SN8 ready for flight and ultimately pulled off a high-altitude launch that made it just a dozen or so seconds (~5%) away from a complete success – far further than anyone really expected. That surprising level of success appeared to lead SpaceX to reevaluate its plans and the strategic design of its test plans.
One result was observed in publicly-visible labels SpaceX uses to identify the dozens of Starship parts in work at any given moment: after SN12, only a few minor unfinished parts of SN13 and SN14 were ever spotted, departing from the flood of activity observed while building SN8 through SN11. In November, CEO Elon Musk revealed that “major upgrades” were planned for Starship SN15 and all subsequent prototypes.
The implication was that SpaceX had already written off no fewer than three Starships (SN8-SN10) to prove that a new, exotic approach to rocket landings could work as planned. If those three failed, SpaceX could likely use Starships SN11 through SN14 – likely enough prototypes to either succeed or conclude that a redesign is necessary. Ultimately, after Starship SN8’s spectacular success and last-second failure, SpaceX seemingly concluded that it was unlikely to need a full seven prototypes to achieve the first soft landing(s) and effectively killed Starships SN12, SN13, and SN14 in the cradle.
SpaceX likely concluded that SN8 had demonstrated that a vast majority of Starship’s existing design was already sound, reducing enough risk to confidently begin major upgrades – akin to building a more permanent structure only after ensuring that the foundation is stable. Indicating exactly that, SpaceX has already begun stacking Starship SN15 and has been churning out hardware for SN16, SN17, and SN18 for the last few months.
That ultimately means that one or more upgraded Starships will likely be ready to carry the torch forward as soon as SN10 and SN11 flight testing comes to an end – whether that means continuing recovery attempts or pushing the envelope higher and faster after the first successful soft landing(s).
The nature of those “upgrades” remains unclear beyond apparent fit-and-finish improvements and the possibility of a more easily manufacturable nosecone design, but it’s clear that things will become clearer far sooner than later at SpaceX’s current rate of progress.
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
