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SpaceX fires up Starship rocket twice in 30 hours ahead of next big tests
SpaceX has successfully fired up a full-scale Starship rocket for the second time in barely 30 hours and removed the ship’s Raptor engine to perform an additional suite of “cryo testing”.
Around 7pm CDT on May 6th, SpaceX technicians began loading the fourth full-scale Starship with liquid oxygen and methane, filling up a large portion of its massive propellant tanks. Just the latest in a line of several tests involving wet dress rehearsals (WDR) completed in the days prior, this test would soon become exceptional. About an hour and a half after work began, Starship SN4’s lone Raptor engine ignited and burned for ~3 seconds, marking the first time in history a next-generation SpaceX rocket truly came alive with one of the engines designed to take it all the way to orbit.
In line with tests performed with Starhopper – a low-fidelity, subscale tested that flew twice with Raptor – last year, it would have been business as usual if SpaceX had called it a day and moved on to something else with Starship SN4. Instead, Starship performed another WDR and fired up its Raptor engine for a second time in just 30 hours after SpaceX teams inspected the rocket and cleared it for another round. It’s unknown why two back-to-back static fires were performed but, to be clear, every step Starship SN4 takes forward is a step into uncharted territory. Already, the ship’s next steps could come as soon as Friday, May 8th.
According to CEO Elon Musk, SpaceX’s second Starship SN4 static fire test was completed successfully and actually marked the operational debut of a critical aspect of the next-generation launch vehicle and spacecraft. Known as header tanks, Starship needs two smaller secondary propellant tanks to complement its main tanks, a need driven mainly by the challenges of landing such a large and mobile spacecraft. Smaller header tanks will also make it dramatically easier for SpaceX to insulate cryogenic propellant and ensure it remains liquid over long-duration cruises in space, but safe and reliable landings are a more pressing concern for these early prototypes.
During landing operations, the main benefits smaller header tanks offer are relative ease of pressurization (needed to safely feed Raptor engines) and a much lower risk of issues from sloshing, which can introduce bubbles and voids that can obliterate rocket engines if ingested. Impressively, per Musk, Starship SN4 completed its second static fire test using its internal liquid methane header tank – a sort of bubble attached to the bottom of the main methane tank dome.
Starship’s liquid oxygen header tank is situated at the tip of the conical nose section, a part that all full-scale ships have been tested without thus far. However, the use of the fuel header tank on May 7th means that Starship SN4 already has a functional, plumbed header tank installed, verifying the partial functionality of a critical part of the next-generation launch vehicle. A second static fire will have also provided SpaceX a wealth of extra data about Raptor’s performance while installed on Starship, invaluable at such an early stage of integrated testing.
Two Starship static fires now under its belt, SpaceX removed SN4’s Raptor engine around 12 hours after its second test and returned it to storage at the company’s nearby factory facilities. According to public notices provided by Cameron County, Texas officials, SpaceX’s next Starship SN4 activity is expected to occur on May 8th with backup windows on the 9th and 10th and will involve “cryo testing”.
The most obvious conclusion is that SpaceX – having completed enough static fire testing to verify Starship SN4’s performance – now wants to really put the rocket through its paces with another cryogenic test. Completed on April 26th, the ship’s first cryogenic ‘proof’ test maxed out at around 4.9 bar (70 psi), enough for low-stress hop tests but well short of the sustained pressure needed for orbital spaceflight. While testing singular propellant tanks in the first few months of 2020, Musk revealed that SpaceX was targeting a minimum of 6 bar (~90 psi) for orbital Starship flights – ~8 bar (115 psi) with a 25% safety factor.
The company actually achieved 8.4 bar with one of its Starship test tanks, the same processes of which were used to build Starship SN4, but a full-scale ship has yet to demonstrate those pressures. Now, SpaceX already has a fifth full-scale prototype (Starship SN5) likely just a week or so away from pad readiness, meaning that Starship SN4’s potential destruction during pressure testing wouldn’t have a big impact on plans for a series of imminent flight tests. If SN4 survives pressure testing, it would likely have its Raptor engine reinstalled and move on to a 150m (500 ft) hop test.
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
