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SpaceX CEO Elon Musk's latest Starship photos reveal surprise landing legs [confirmed]
Update: In a Twitter response to Teslarati’s report, Musk confirmed that SpaceX has already installed six telescoping landing legs on the Starship SN3 prototype.
CEO Elon Musk published new photos of a Starship prototype shortly after it was moved to SpaceX’s South Texas launch pad, revealing the surprise inclusion of already-installed landing legs and hinting at the growing maturity of the rocket’s design.
Published on March 30th and likely taken late on March 29th, Musk’s latest Starship photos offer the best look yet at the massive vehicle’s engine section, where Raptor engines may soon be installed for historic static fire and hop test attempts. First captured in photos taken by local photographer and resident Mary (bocachicagal) on March 28th, speculation about what appeared to be six odd legs immediately kicked off on spaceflight forums. Due to limited publicly-available perspectives and the appendages’ locations inside Starship’s cavernous engine section, there was some limited ambiguity as to whether the steel pieces were truly legs or something closer to general structural support.
Thankfully, Musk’s new photos all but confirmed the former theory, revealing a sextet of hinged legs with a curious stubby appearance and what appears to be a rather simple and elegant design. Most importantly, the unexpected presence of landing legs – while likely cheap to implement – suggests that SpaceX is growing increasingly confident in each subsequent Starship prototype, an encouraging sign for imminent static fire and hop test plans.
In fact, SpaceX filed a Notice to Airmen (NOTAM) with the Federal Aviation Administration (FAA) on March 30th — the biggest confirmation yet that the company is seriously working to prepare Starship SN3 for a Raptor engine static fire test as early as April 1st. Backup dates on the 2nd, 3rd, and 4th are included, leaving a decent amount of breathing room for SpaceX’s Texas team to (hopefully) successfully complete the rocket’s proof test in the next few days.
Possibly preceded by a water pressure test to check for leaks and verify general structural integrity, Starship SN3’s proof test will see the rocket’s methane and oxygen tanks fully filled with cryogenic liquid nitrogen. The tank pressure would then be increased to around 6-8 bar (90-115 psi) to ensure that Starship can handle the thermal and pressure stresses it will experience during launches. Given SpaceX’s recent history, including a partially unintentional Starship Mk1 tank failure in November 2019, the intentional destruction of two Starship test tanks in January 2020, and Starship SN1’s unintentional February 2020 failure, success is still far from guaranteed for Starship SN3.
Nevertheless, SpaceX seems more confident in Starship SN3 than it was in Starships Mk1 and SN1 – the only other full-scale prototypes to have reached the testing phase. It’s possible that including leg prototypes were cheap and easy enough to be worth installing regardless of SpaceX’s broader confidence in Starship SN3 as a whole. However, it would still be a clear waste of time and resources to install all six landing legs if the internal consensus was to expect a failure in the early phases of SN3 testing.
SpaceX, in other words, seems to believe that Starship SN3 will pass its imminent tank proof test without any major issues. Additionally, the company must be confident in the outcome of the Starship SN3 Raptor static fire(s) expected to immediately follow any successful proof test. SpaceX has successfully demonstrated Raptor several times on flight hardware with the help of the Starhopper development vehicle, but a full-scale Starship is arguably a different animal.
Regardless, it’s now clearer than ever that SpaceX is confident enough to put a few eggs in the Starship SN3 basket. With landing legs installed, the massive rocket prototype could be ready for a Starhopper-style 150m (500 ft) hop test just a week or so from now. For now, though, Starship SN3 needs to pass a tank proof test, perform a wet dress rehearsal (WDR) with real propellant, and complete one or several Raptor static fires before a flight test will be in its cards. Stay tuned!
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
