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SpaceX stacks Starship nose section for the first time in months
SpaceX has stacked a Starship nosecone section to its full height for the first time in almost a year, featuring an upgraded design that could soon support an ambitious series of flight tests.
Back in August 2019, SpaceX first began stacking the nose section of Starship Mk1 – the first full-scale prototype of any kind. It became clear a few months later that Starship Mk1 was more of a rough proof of concept than a full-fidelity test article, but it still became the first (and only, so far) Starship to reach its full ~50m (~160 ft) height. After serving as a centerpiece during CEO Elon Musk’s September 2019 Starship presentation, SpaceX removed the nose and attempted to test the Mk1 tank section itself, ultimately destroying the ship.
Now eight months distant from Mk1’s demise, SpaceX’s Starship R&D program has entered the prototype mass-production phase. Since January 2020, SpaceX has built five upgraded Starship tank sections (and tested three to destruction), built and tested four stout test tanks, and completed at least 4-5 new nosecone prototypes. For the first time since nosecone production began several months ago, one of the noses has finally been stacked to its full height atop five steel rings.
At the moment, SpaceX is hard at work preparing Starship SN5 for its first wet dress rehearsals (WDRs) with methane and oxygen propellant and either one or several Raptor engine static fire tests. If successful, SpaceX will quickly move to flight test preparations, readying SN5 for a nominal ~150m (~500 ft) hop, though the company is technically no longer restricted to that ceiling. For such a low-altitude test, aerodynamic features like a nosecone or flaps serve no functional purpose, meaning that SN5 is unlikely to ever receive those additions.
Roughly two miles west of the coastal launch and test site SN5 is stationed at, SpaceX has already more or less finished Starship SN6, although the newest ship’s fate is unclear. Pictured above on July 10th, the task of stacking an even newer ship (likely SN8) may already be underway. Last month, SpaceX tested a new ‘test tank’ built out of a different steel alloy said by CEO Elon Musk to be theoretically superior. Two cryogenic pressure tests seemingly confirmed that suspicion, proving that 304L stainless steel fails more gracefully than 301 while still offering similar strength at the pressures Starships operate at. The SN7 test tank was built and tested around the same time as SpaceX was finishing up SN6, implying that the ship was almost certainly built out of 301 steel.
If 304L really is the way forward for future Starship prototypes, the next step will be building an entire ship out of the steel alloy and performing a full cryogenic proof test and wet dress rehearsal. Given that SN5 and SN6 are likely identical (or nearly so), SN6 may have been made redundant before the ship even left the factory floor.
This is all to say that it’s a bit of a mystery where the first upgraded nosecone will find itself in the coming weeks. Like SN6 or SN7, it could either be redundant on arrival, built as practice, or both. It could also be the first nosecone installed on a flightworthy Starship prototype. It’s unlikely but not impossible that SN5 survives its static fires and first hops and is modified to support three Raptors and aerodynamic control surfaces, while SN8 and SN9 are more probable candidates for the first high-altitude, high-velocity test flight(s). SpaceX has at least 3-5 more Starship nosecones strewn about its Boca Chica factory, though, so odds are good that the first new nose section to reach full height won’t be the first to take flight.
For now, Starship SN5 (sans nose) is scheduled to attempt its first wet dress rehearsal (WDR) no earlier than July 16th. If successful, a static fire could follow a few days after that and a hop test another few days later.
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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
