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SpaceX recaps historic Starship landing in 4K as next ship readies for flight
SpaceX has published a new 4K video recapping Starship’s first intact landing after a high-altitude launch right as the company is preparing the next ship for flight.
On March 3rd, Starship serial number 10 (SN10) briefly became the first prototype to successfully launch to 10 km (6.2 mi), ‘skydive’ back to Earth, flip around, and land in one piece. Put simply, Starship SN10 made it unequivocally clear that the exotic, unproven method of landing selected by SpaceX could be made to work. Unfortunately, while Starship SN10 did land in one piece, the landing was much harder than planned.
Due to some combination of that hard landing and an apparent onboard fire that started in the last ~20 seconds of flight, SpaceX only had around six minutes to contemplate its success before Starship SN10’s propellant tanks were breached, violently depressurizing the rocket and causing a large explosion and fire.
Previously discussed on Teslarati, SpaceX CEO Elon Musk later took to Twitter to offer some educated guesses as to why Starship SN10 exploded.
“Starship SN9 ultimately failed a few seconds earlier than Starship SN8 when one of its Raptor engines failed to ignite, precluding a true flight test of the helium pressurization fix. As it turns out, Musk believes that that very fix may have doomed Starship SN10.
As Starship SN10 forged ahead past the points of failure that killed SN8 and SN9, the SpaceX CEO thinks that one or more of the vehicle’s three Raptor engines began to ingest some of that helium as they drained the methane header tank. As a result, engine thrust fell below expected values, preventing Starship SN10 from fully slowing down for a soft landing. Instead, the Starship hit the ground traveling a solid 25 mph (~10 m/s), obliterating its tiny landing legs and damaging its skirt section.”
Teslarati.com – March 10th, 2021
In other words, the losses of Starships SN8, SN9, and SN10 all share a relatively common point of failure – propulsion reliability. Technically, only Starship SN9’s failure can be blamed specifically on Raptor, one of which failed to ignite during its flip and landing maneuver. SN8 and SN10 both failed because of issues in the complex network of plumbing and pressurization systems responsible for feeding Raptors the right amount of propellant.
For SN8, the ship’s pressurization system failed to provide the necessary fuel head pressure at the last second, starving the Starship’s Raptors. SN10 ironically failed because the quick fix inspired by SN8’s failure – partially replacing a methane pressurant with helium – likely contaminated its methane fuel with helium, effectively watering down Raptor’s performance. While likely frustrating for SpaceX, the failures are still extremely valuable and loss of hardware remains a routine and intentional part of the company’s approach to iterative rocket development.
On the plus side, the FAA has already cleared SpaceX’s next Starship for flight after SN10’s momentary success and subsequent explosion. Spurred by that brief taste of total success, SpaceX wasted no time to prepare that next prototype – Starship SN11 – for flight and rolled the rocket to the launch pad mere days after SN10’s March 3rd flight. That very same day, SpaceX completed ambient pressure testing – a basic verification that Starship SN11 is leak-free.
A few days later, SN11 appeared to pass its first cryogenic proof test, replacing room-temperature gas with cryogenic liquid nitrogen. Three days after that, SpaceX attempted to put the Starship through its first triple-Raptor static fire test but appeared to suffer an abort milliseconds after a partial ignition of one or two of its three engines. Starship SN11 briefly caught fire and burned for at least 20-40 seconds after the abort, unsurprisingly triggering several days of delays. Nevertheless, if SN11 can make it through a second static fire attempt without issue on Thursday or Friday, the Starship is still well on track to take flight weeks earlier than any of its predecessors.
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
