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SpaceX Starship passed “cryo proof” test for the first time and here’s what’s next
Elon Musk says a SpaceX Starship prototype has passed a critical “cryo proof” test for the first time, opening the door for the rocket to move on to even bigger tests.
Late on April 26th, SpaceX’s South Texas team (and possibly a console team in California) readied the fourth full-scale Starship prototype (SN4) for its second major test. Known as a cryogenic proof test, it began less than 24 hours after the rocket completed a room-temperature gas pressure test to check for leaks and verify that the pressure vessel was sound. Musk quickly confirmed that Starship SN4 passed through that “ambient proof test” without issue.
For the cryo proof test, room-temperature nitrogen gas was replaced with ultra-cold liquid nitrogen, serving as a chemically neutral (i.e. non-explosive) simulant for Starship’s liquid oxygen and methane propellant. After a few hours of partial loading and offloading cycles meant to ensure that Starship’s valves and propellant supply hardware was working as intended, SpaceX controllers fully filled the rocket with some ~1000 metric tons (2.2 million lb) of liquid nitrogen. Once full, a hydraulic ram setup was activated to exert forces akin to Raptor engines operating at full thrust. After several prior failures, Starship SN4 thus became the first to survive the ordeal and graduate into the next stage of testing.
According to CEO Elon Musk, that next step will be a static fire test with a lone Raptor engine installed. Able to produce at least 200 metric tons of thrust (~450,000 lbf) at full throttle, Raptor is an exceptionally efficient methalox (methane/oxygen) rocket engine designed by SpaceX to power Starship and its Super Heavy booster. Methane and oxygen was chosen in large part because of the relative potential ease of its extraction and refinement on Mars.
Per Musk, that static fire could occur within the next six or so days, meaning that SpaceX will likely install a functional Raptor engine on a full-scale Starship for the first time ever within the next day or two. Before a static fire can be performed, though, another significant test or two will have to be completed.
Known as a wet dress rehearsal (WDR), the first of those tests will be similar to April 26th’s cryo proof but with the neutral liquid nitrogen placed by real liquid oxygen and methane propellant. This is much riskier than the cryo proof in the sense that if a tank failure were to occur or a fire to accidentally start, 1000+ tons of highly-pressurized propellant could easily create a massive explosion and fireball, destroying or damaging much of the surrounding pad equipment. The WDR could potentially be rolled into another Raptor engine test that would verify its preburner performance.
To operate, Raptors first take liquid oxygen and liquid methane into separate parts of the engine and rapidly heat them to turn them into high temperature gas. Those preburners then send that hot gas to separate turbopumps that spin up and allow the engines to keep supplying themselves with large quantities of propellant, followed by the process of actually igniting the engine itself with a complex series of blowtorches.
If the preburner and turbopump spin-up test is successful, SpaceX can then move on to the actual static fire. Featuring a single Raptor engine, Starship SN4 will hopefully become the first full-scale rocket to safely operate a flight-grade engine since SpaceX began full-scale tests in November 2019. If successful, that static fire could pave the way for Starship SN4 to perform a Starhopper-style 150m (500 ft) hop test as early as May 2020 – a hop that would be powered by a single Raptor engine according to Musk.
Starship SN5 will reportedly be the first ship to both have a nosecone installed and three Raptor engines installed if SN4 has a very successful few weeks and that new ship is perhaps just 5-10 days from being fully assembled. In short, things are about to get very busy and very exciting at SpaceX’s South Texas Starship factory and launch pad.
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
