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SpaceX’s first high-altitude Starship fitted with flaps and rolled to the launch pad
After a four-day delay, SpaceX has successfully installed the first high-altitude Starship at its Boca Chica launch pad not long after the rocket was outfitted with large flaps.
Technically the second time a Starship was outfitted with flaps, Starship serial number 8 had the bottom half of its aerodynamic control surfaces installed on September 23rd – exactly one year after Starship Mk1’s flaps were first installed. Starship Mk1’s flaps were likely meant to be functional but SpaceX never appeared to activate them and Mk1’s main body (tank section) was destroyed during a November 2019 pressure test, failing far before the necessary pressures for flight tests. As such, barring a surprise or two, Starship SN8 will very likely become the first flightworthy prototype to have functional flaps installed.
That remains to be seen, though, and will be put to the test over the next few weeks. If all goes according to plan, the ship could become the first to attempt a high-altitude, 15 km (9.3 mile) launch and landing testing, likely also becoming the first Starship to break the sound barrier.
Starship SN8’s first steps toward testing began on September 26th when SpaceX loaded the rocket onto a self-propelled mobile transporter (SPMT) and rolled it to the company’s dedicated Boca Chica launch and test facilities. Shortly after arrival, a crane and load spreader was attached to the rocket to lift it onto one of the pad’s test stands (Stand A). That lift never came and the crane eventually detached and retracted, kicking off what would become an unusual four-day delay.
It’s believed that the relatively high winds on the Boca Chica coast were to blame, creating conditions that were too hazardous to risk the precise, hands-on work required to lift and manipulate a ~70 metric ton (~150,000 lb) rocket. While undeniably heavy, an empty Starship’s huge surface area effectively turns it into a giant sail, catching and amplifying wind gusts. Attaching a Starship to a launch mount’s hold-down clamps likely demands millimeter precision, making installation and high winds obviously incompatible (or at least inadvisable).
Finally, around midnight on September 30th, winds died down in Boca Chica and SpaceX fired up a waiting crane and lifted Starship SN8 onto the launch mount. Soon after, technicians began the process of installing the mount’s temporary hydraulic ram – used to mechanically simulate engine thrust – to the rocket’s ‘thrust puck’.
Like every Starship prototype since Mk1, Starship SN8’s first major challenge will involve passing an acceptance test known as a “cryogenic proof.” After being pressurized with ambient-temperature nitrogen gas to check for leaks, SN8 will be fully filled with liquid nitrogen while the hydraulic ram subjects its thrust puck and engine section to stresses similar to the thrust of three Raptor engines. Together, three Raptors are capable of producing more than 600 metric tons (1.3 million lbf) of thrust. For reference, four Raptors would effectively match the thrust of an entire Falcon 9 booster with all nine Merlin 1Ds at full throttle.
If SN8 reaches the necessary pressure and survives the stress of its cryo proof(s), it will likely become the first Starship to attempt a triple-Raptor static fire – a first for the engine, too. Starship SN8’s first cryo proof attempt is scheduled no earlier than 9pm-6am CDT (UTC-5) on Sunday, October 4th with backup windows on the 5th and 6th. The first static fire attempt – possibly beginning with one Raptor or jumping straight to three – could happen several days after a successful cryo proof.
According to Elon Musk, SpaceX will static fire SN8 twice before attempting its 15 km (~50,000 ft) launch debut. More likely than not, SpaceX will attempt a triple-engine static fire with the Starship as-is, install SN8’s nosecone and forward flaps, and attempt a second static fire while only drawing propellant from tbe rocket’s smaller header tanks (one of which is located in the tip of its nose). Only time (or Elon tweets) will tell.
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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.”
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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
