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SpaceX’s orbital Starship launch debut could still happen this year

A senior SpaceX engineer and executive believes that Starship's first orbital launch could still happen by the end of 2020. (SpaceX)

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Despite the spectacular demise of a full-scale prototype just days ago, a senior SpaceX engineer and executive believes that Starship could still be ready for its first orbital launch attempt before the end of the year.

Even if the first launch attempt fails, that milestone – if realized – would be one of the single biggest upsets in the history of spaceflight, proving that Saturn V-scale orbital-class rockets can likely be built in spartan facilities with common materials for pennies on the dollar. Much like Falcon 1 suffered three launch failures before successfully reaching orbit, there’s a strong chance that Starship’s first shot at orbit will fall short, although each full-up launch failure would likely cost substantially more than the current prototypes being routinely tested to destruction in South Texas.

Most recently, what CEO Elon Musk later described as a “a minor test of a quick disconnect” went wrong in a spectacular fashion, causing a major liquid methane leak that subsequently ignited and created a massive explosion. Although Starship SN4 did technically complete its fifth Raptor engine static fire test just a minute or so prior, the ship and its immediate surroundings were obliterated by the violent explosion, leaving little more than steel shrapnel and the broken husk of a launch mount behind. It’s in this context that one of SpaceX’s most levelheaded, expert executives believes that an orbital launch could still happen this year.

A senior SpaceX engineer and executive believes that Starship’s first orbital launch could still happen by the end of 2020. (NASASpaceflight – bocachicagal)

While Starship SN4’s demise and the continued possibility of the ship’s orbital launch debut occurring less than seven months from now may seem at odds with each other, that’s actually just a side effect of the approach SpaceX has always taken when developing brand new rockets and spacecraft. Following the lead of the scrappy teams that used the exact same methods to design, test, and fly the massive Saturn rockets that took humans to the Moon, SpaceX has always preferred to learn by doing.

Inevitably, testing minimum viable products to their limits will lead to failures, but those failures are actually extremely valuable so long as they are extensively analyzed and learned from. That’s exactly what SpaceX has been doing for the last six or so months with full-scale Starship prototypes: building, testing, failing, and improving in an unending cycle. Built slowly with inferior methods, Starship Mk1 almost immediately during its first pressure test in November 2019. SpaceX took that failure, extracted all the insight it could, and dramatically improved its production methods before completing Starship SN1 barely three months later.

On November 20th, 2019 Starship Mk1 burst during its first major cryogenic pressure test. (NASASpaceflight – bocachicagal)
In January, SpaceX built and tested two ‘test tanks’ to failure. (NASASpaceflight – bocachicagal)
Starship SN01 failed on February 28th because of a faulty ‘thrust puck’, later rectified with a third test tank that became the first to survive pressure testing just 10 days later.(NASASpaceflight – bocachicagal)
Starship SN3 was destroyed by an improper test procedure on April 3rd. (LabPadre)
Starship SN4 marked the most recent failure during SpaceX’s hardware-rich development program.

Prior to SN1, SpaceX built and tested two stout test tanks to failure, ultimately achieving pressures of ~8.5 bar – sufficient for reliable human spaceflight – with the second tank on January 30th, 2020. On February 28th, Starship SN1 was unfortunately destroyed by a faulty ‘thrust puck’ (Raptor engine mount). Just 10 days later, SpaceX successfully tested a third ad-hoc test tank, proving that it had already rectified the engine section design flaw. Hardware isn’t always the only problem, however, and Starship SN3 was destroyed by human operator error during a cryogenic proof test on April 3rd.

Starship SN4 was completed and moved to the launch pad less than a month later and began testing just a few days after that, quickly racking up milestones as it became the first full-scale prototype to pass cryogenic proof testing, perform a wet dress rehearsal (WDR) with real propellant, fire up a Raptor engine, and complete a more ambitious cryogenic pressure test. Prior to the ground systems fuel leak that killed it, SN4 was possibly just days away from attempting the inaugural flight of a full-scale Starship prototype.

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With Starship SN4 now steel confetti, Starship SN5 – effectively complete – will likely take over where its predecessor left off, heading to the launch pad within the next week or so before attempting a cryogenic pressure test and Raptor static fire to clear it for flight. Per Koenigsmann, that flight debut could come just a few weeks from now – likely before the end of June if replacement ground equipment can be quickly completed. If Starship SN5 survives that hop debut, it may ultimately be upgraded with a nosecone, flaps, and two additional Raptor engines to perform a dramatic 20 km (~12 mi) flight, capped with a supersonic skydiver-style reentry and landing test.

Once that capability has been successfully demonstrated, Super Heavy development and orbital Starship operation and reentry are the next critical hurdles. If Koenigsmann is correct, it’s safe to say that the first fully heat-shielded Starships and the beginnings of the first one or several Super Heavy booster prototypes will begin to appear in South Texas within the next few months.

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Eric Ralph is Teslarati's senior spaceflight reporter and has been covering the industry in some capacity for almost half a decade, largely spurred in 2016 by a trip to Mexico to watch Elon Musk reveal SpaceX's plans for Mars in person. Aside from spreading interest and excitement about spaceflight far and wide, his primary goal is to cover humanity's ongoing efforts to expand beyond Earth to the Moon, Mars, and elsewhere.

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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.” 

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Credit: @BLKMDL3/X

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. 

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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.

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Credit: Tesla China

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.

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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.

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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.

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Gage Skidmore, CC BY-SA 4.0 , via Wikimedia Commons

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.

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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.

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