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SpaceX Starship go for nosecone installation after historic static fire
SpaceX CEO Elon Musk has confirmed that Starship and Raptor’s first triple-engine static fire was a success, opening the door for nosecone installation.
Around 3:13 am CDT, October 20th, Starship serial number 8 (SN8) successfully fired up three Raptor engines less than two hours after completing the first successful three-engine preburner test. With zero direct human intervention, SpaceX remotely detanked the rocket’s cryogenic liquid methane and oxygen propellant – the remnants now too warm to be used again in a controlled manner. In an hour or less, SpaceX engineers combed through the data produced and concluded that all three Raptor engines were healthy after their partial ignition test.
Effectively reset to a stable state, SpaceX once again proceeded to load Starship SN8’s propellant tanks with a small amount of supercooled LOx and LCH4, almost exactly mirroring the preburner test. Around 50 minutes after the recycle commenced and 25 minutes after propellant loading kicked off, Starship SN8 ignited three Raptors simultaneously – a major milestone for any rocket engine. Static fire now completed, Starship SN8 has been cleared to become the first operational prototype to reach its full 50m (~165 ft) height.
Shortly before Musk confirmed SN8’s static fire success, SpaceX canceled a preexisting October 20th static fire window and scheduled several new road closures on Wednesday, October 21st. Unlike the company’s recent static fire closures, all but one of which ran from 9pm to 6am, SpaceX’s new Wednesday closures are scheduled from 7am to noon and 3pm to 5pm local (CDT).
While a minor data point, in context with Starship SN8’s static fire success, the closures alone made it clear that SpaceX planned to begin installing Starship SN8’s nosecone on October 21st. Musk confirmed that assumption a few hours after those road closures were published.
It’s not entirely clear but most observers are assuming that Wednesday’s 7am-12pm window is needed to transport a large, new crane the ~2 miles between SpaceX’s Boca Chica factory and launch facilities. Starship SN8’s stacked nose section would then likely be installed on the same self-propelled mobile transporters (SPMT) and rolled to the launch pad from 3pm to 5pm, after which the nose would be lifted and stacked atop Starship SN8.
SpaceX has only fully stacked a Starship prototype once before when Mk1’s nose section was temporarily mated to its tank section to be the centerpiece of CEO Elon Musk’s October 2019 Starship event. It’s unclear why SpaceX wouldn’t simply use one of the mobile cranes its rented for Starship tank section operations (and stacking Mk1) in the past, so it remains to be seen what Wednesday’s road closures will actually be used for.
SpaceX’s road closure plans end with a wildcard, however. Once installed, the plan is to perform a second triple-Raptor static fire while only drawing propellant from SN8’s header tanks – small internal tanks designed to hold landing propellant, one of which is situated at the tip of Starship’s nosecone. On October 21st and 22nd, SpaceX still has two 9pm-6am closures scheduled for “SN8 static fire” testing. Filed early on October 20th, before SN8’s successful static fire, the most likely explanation is a simple clerical error or miscommunication, with Cameron County or SpaceX failing to properly communicate that those subsequent static fire test windows are no longer needed.
If retaining the static fire closures was intentional, it would mean that SpaceX – likely at Musk’s urging – intends to install Starship SN8’s nosecone in a matter of hours. It’s almost inconceivable that Starship SN8’s nosecone – outfitted with multiple gas thrusters, forward flaps powered by Tesla motors, a liquid oxygen header tank, vents, and plenty of plumbing – can be installed and made ready for testing in less than 12 hours. Barring a surprise method of mating SN8’s nose and tank sections, the nosecone will have to be welded to the rest of SN8 and the weld inspected – typically a multi-day process.
Regardless, given how quickly SpaceX moves and how dead-set CEO Elon Musk is at pushing limits and breaking barriers, it seems reasonable to assume that Starship SN8 may be fully integrated and ready for a second static fire test just a handful of days from now. Once completed, SN8 will be ready to attempt Starship’s first high-altitude flight test, launching to ~15 km (~9.3 mi) to attempt an untested skydiver-style descent and landing.
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
