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SpaceX’s next Starship hop a step closer after ‘cryo proof’ test
SpaceX appears to have successfully completed one of three major tests standing between a new Starship prototype and the rocket’s next hop.
Known as a cryogenic proof test (“cryo proof”), signs currently point towards a success on Starship SN6’s first try – albeit an hour or two past the end of the planned test window. The proof was planned between 8 am and 5 pm CDT (UTC-5) on August 16th with identical backup windows on Monday and Tuesday in the event of an abort or delay. Thankfully, in a breath of fresh air after many Starship SN5 test delays, SpaceX had no such need.
With the help of local sheriffs, SpaceX closed the highway around 10:15 am and pressurized Starship SN6 with ambient-temperature gas (likely nitrogen) around half an hour later. As usual, the company took its time while the Starship prototype effectively came to life for the first time. Around 2.5 hours later, the Starship began visibly venting for the first time as it operated dozens of valves to maintain safe tank pressures.
To perform a cryogenic pressure test, SpaceX effectively performs a wet dress rehearsal (WDR) – a test that simulates a full launch flow short of liftoff – with no engine installed. To prevent leaks or hull breaches from turning potentially catastrophic during what is often the first major test of a prototype, SpaceX loads Starship with liquid nitrogen (LN2) instead of liquid methane and oxygen propellant. During that process, Starship’s thin steel skin will quickly drop to arctic temperatures, becoming cold enough that it will literally freeze the water vapor out of any ambient air it comes in contact with.
Around 1 pm local, the first sign of that frost sheath appeared but remained a sliver before disappearing around 2 pm. Starship SN6 then hung around for an hour before testing activities appeared to restart. Close to 5:40 pm, almost an hour after SpaceX’s August 16th window was meant to close, frost reappeared on Starship SN6’s hull and rapidly crept up the side of the massive rocket.
Starship SN5’s own cryo proof test – completed on June 30th – debuted apparent upgrades to SpaceX’s South Texas launch facilities, loading the rocket with hundreds of thousands of gallons of LN2 in 15-20 minutes. The ability to load huge quantities of cryogenic propellant very quickly will be critical for SpaceX, as Starship’s efficiency will decrease substantially as its propellant warms. Along those lines, Starship SN6 became the second prototype to be rapidly loaded with liquid nitrogen, going from nearly empty to nearly full in ~15 minutes.
SN6 detanked over the next hour or so and SpaceX opened the road and had a team back on the pad to inspect the rocket by 7:40 pm. At some point during the test, SpaceX likely actuated hydraulic arms attached to Starship’s engine section to simulate the stresses of Raptor thrust under cryogenic loads. Either way, SpaceX was apparently satisfied with the results of Starship SN6’s first cryo proof and proceeded to cancel two backup windows scheduled on August 17th and 18th – a consistent sign that things either went very right or very wrong.
In the case of SN6, nothing was distinctly amiss or different during its cryo proof, pointing towards a successful test. If that’s the case, SpaceX will begin removing the hydraulic Raptor simulator to install an actual Raptor engine and will scheduled road closures for an imminent static fire test. Prior to that actual Raptor ignition test, SpaceX may choose to perform a wet dress rehearsal (WDR) on its own or partially test Raptor by igniting its preburners to momentarily spin up its turbopumps. The company could also integrate both of those precursor tests into the same window as the static fire itself.
If those tests go according to plan, Starship SN6 could be ready for SpaceX’s second full-scale hop ever just a week (or less) later. CEO Elon Musk says that the company’s current goal is to perform multiple Starship tests until the process is fast, smooth, and consistent.
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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
