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SpaceX’s high-altitude Starship launch debut unlikely before Crew-1
Update: SpaceX canceled its November 5th and 6th Starship SN8 static fire test windows on Thursday, delaying the next Starship test window to November 9th unless additional testing is scheduled on the 7th and 8th.
As previously discussed, SpaceX requested three road closures for “Starship SN8 Static Fire and 15KM Flight” attempts on November 9th, 10th, and 11th on Wednesday. With recent cancellations, NASASpaceflight reporter Michael Baylor says that the odds that Starship SN8 will be ready to fly before SpaceX’s Crew-1 operational NASA astronaut launch debut (NET November 14th) are now minuscule, further indicating that each of the three upcoming test windows will be dedicated to one or more Raptor static fires.
Stay tuned for updates as SpaceX continues to prepare Starship for its most ambitious, challenging, and risky test yet.
In the form of road closure filings, SpaceX has effectively announced the first possible dates for Starship’s high-altitude launch debut, a high-risk test that CEO Elon Musk recently made clear could fail.
Per road closures published on SpaceX’s dedicated Cameron County, Texas page, Starship serial number 8 (SN8) could apparently be ready for its historic launch debut as soon as November 9th in a 12-hour window that opens at 9am CST (15:00 UTC). Identical 9am-9pm windows on November 10th and 11th will serve as backups in the event of one or several launch aborts or delays – fairly likely for a prototype as complex as Starship SN8.
However, several tests stand between SN8 and flight-readiness, further increasing the odds of delays as SpaceX continues to work out the kinks in what amounts to the first fully-assembly, functional Starship.
Musk has already stated that Starship SN8 will need to complete another Raptor static fire test – potentially with one, two, or three engines – before SpaceX will consider the rocket ready for its flight debut. Over the last few days, NASASpaceflight.com reporter Michael Baylor has noted on livestreams that multiple more static fire tests are actually in order before SpaceX will attempt to launch Starship SN8. It’s currently unclear what the purpose of those additional static fire tests is, given that SN8 has already completed a triple-engine Raptor static fire.
In the two weeks since that milestone, however, SpaceX did take a major step forward, mating Starship SN8’s nose section to create what is effectively the first full-scale, functional prototype. Aside from two smaller forward flaps and attitude control system (ACS) cold gas thrusters, that nose section also contains a small secondary liquid oxygen tank known as a header tank – meant to store a small amount of highly pressurized propellant to be used during Raptor reentry and landing burns. Several months back, Musk revealed that Starship SN4 completed a static fire while only feeding on fuel (liquid methane) stored in the rocket’s methane header tank, making it reasonable to assume that SpaceX wants to repeat a similar test with SN8 while using both fuel and oxidizer header tanks.
For Starship SN8, those header tanks will be an irreplaceable necessity during the rocket’s first attempted launch, free-fall, flip maneuver, and landing. In a clear sign of preparation for a header-tank-only static fire test, SpaceX appeared to successfully complete a cryogenic proof of Starship SN8’s newly-installed nose section and nose (LOx) header tank on November 3rd, verifying that liquid nitrogen – standing in for LOx – can be pumped more than 50 meters (~165 ft) from Starship’s launch mount to the tip of its nose to load said tank.


SpaceX has one more “SN8 nose cone cryo proof” test window scheduled from 8am to 5pm CST Thursday, November 5th that could be used for one or more of those expected static fire tests. Otherwise, SpaceX’s Starship SN18 15 km (~50,000 ft) launch closures were technically filed for an “SN8 Static Fire and 15 KM Flight,” allowing SpaceX to perform one or several static fires before attempting to launch. All things considered, the odds that Starship SN8 will launch on time between November 9th and 11th are probably less than 50:50, but there is definitely a chance.
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.