News
SpaceX Starship destroyed during cryo test but the next ship is already on the way
SpaceX’s third full-scale Starship prototype has followed a little too closely in the footsteps of its predecessors, suffering a catastrophic failure during its first cryogenic test.
On April 2nd, SpaceX successfully put Starship SN3 through an ambient temperature pressure, allowing the ship to take its first breaths and ensuring that no leaks were present in its massive propellant tanks. Just a handful of hours later, Starship SN3 began its first attempted cryogenic proof test. Neutral liquid nitrogen was loaded into the ship’s liquid oxygen (LOX) tank for a brief period before SpaceX aborted the test due to frozen valves in the ground support equipment (GSE) tasked with feeding the rocket — confirmed by CEO Elon Musk around 7:30 pm PDT.
Around six hours after the first attempt, SpaceX presumably managed to alleviate GSE valve issues and began Starship SN3’s second attempted cryogenic proof test around 11pm local (04:00 UTC). While things started out somewhat normally, they did not end well for the rocket prototype.
For unknown reasons, SpaceX began the second cryo test attempt by only loading Starship’s upper (LOX) tank with supercool liquid nitrogen. Given that Starship is constructed out of stainless steel sheets only slightly thicker than two US quarters, the lower (methane) tank would have almost certainly had to be pressurized, too, likely relying on gaseous (ambient temperature) nitrogen. Already, for a rocket built out of near-continuous metal, that temperature differential could pose a major problem.
Still, for the better part of three hours, things seemed to go exactly as planned, with the rocket venting dozens of times and the upper tank visibly developing a coating of frost as it began to freeze the water vapor right out of the humid Texas air. Alas, around 2:07am local (07:07 UTC), things took a turn for the worse. The unfilled methane tank below the now-LN2-laden LOX tank appeared to crumple, beginning at a small dent that appeared over the course of the test. Gravity took over a few seconds later, further crumpling the methane tank and causing the top-heavy rocket to tip over and the LOX tank to burst.
While admittedly from the armchair, not a lot of this particular failure makes sense. If the bottom methane tank were significantly pressurized with gaseous nitrogen, a rapid loss of structural integrity would have likely been a far more violent ordeal as the gas attempted to escape. Instead, the failure was – relative to the possibilities – extremely gradual. In fact, it almost appeared as if the bottom methane tank was either never actually pressurized or not pressurized nearly enough to withstand the weight of several hundred tons of liquid nitrogen. Given SpaceX’s expertise and familiarity with rocketry, that option thankfully seems vanishingly unlikely.
All other possible explanations are at least as hard to parse, leaving it up to SpaceX or CEO Elon Musk to clarify what transpired if they choose to do so.
On a more positive note, SpaceX has continued to churn out steel rings and bulkheads and assemble them into sections of Starship SN4 – the rocket’s next full-scale prototype – for the last two or so weeks. If Starship SN1, SN2, and SN3 are anything to go by, the fourth full-scale Starship prototype could be ready to head to the pad for testing just a handful of weeks from now, picking up where Starship SN3 left off. Thankfully, the latter rocket’s April 3rd failure appears to have been relatively benign as far as pad hardware goes, likely requiring minimal repair work to be ready for its next test campaign.
While unfortunate, it’s critical to remember that this is all part of SpaceX’s approach to developing new and unprecedented technologies. Be it Falcon 1, Falcon 9 booster recovery, or Falcon 9 fairing recovery, all groundbreaking SpaceX efforts have begun with several consecutive failures before the first successes – and the first streaks of consecutive successes. Given Musk’s September 2019 claim that SpaceX is putting just ~5% of its resources into Starship, prototypes like Mk1, SN1, and SN3 are being fabricated for pennies on the dollar.
As a schedule setback, SpaceX is building ships so quickly that any single prototype failure shouldn’t cause more than a handful of weeks of delays, and the goal is to produce an entire Starship every week by the end of 2020. For now, SpaceX will hopefully learn from each failure during developmental testing and roll those lessons learned into each future prototype.
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.”
News
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
