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SpaceX’s second Starship hop imminent after Raptor static fire test
SpaceX has successfully fired up a new Starship prototype’s Raptor engine, putting the company on track for its second Starship hop test as soon as this week.
The milestone comes not long after SpaceX Starship serial number 6 (SN6) completed its first cryogenic proof, a pressure test with liquid nitrogen (LN2) used to safely verify the structural integrity of tanks (and rockets, in particular). Measuring 9m (30 ft) wide and some 30m (~100 ft) tall, SpaceX rolled Starship SN6 from its Boca Chica, Texas factory to a nearby test and launch facility on August 11th and wrapped up its first acceptance test on August 16th.
Now, just seven days after its cryo proof, SpaceX has installed a new Raptor engine (SN29), prepared SN6 for a much riskier round of tests, and completed a static fire with said engine, leaving just one major step between the Starship and its hop debut. Of course, the process still had its fair share of hiccups.
SpaceX’s first SN6 static fire test window – published by Cameron County in the form of road closure notices – was set for 8 am to 8 pm CDT (UTC-5), August 23rd a few days after the Starship’s cryo proof. The first test attempt began around 9:30 am but was aborted soon after as SpaceX employees returned to the launch pad to (presumably) troubleshoot. The second attempt began around 2:30 pm, leaving a little less than half the test window available.
Attempt #2 very nearly managed to extract a static fire, aborting possibly a second or less before Raptor ignition around 3:41 pm. Once again, SpaceX teams returned to the pad after Starship was detanked and safed, briefly inspecting the general location of the rocket’s Raptor engine before once again clearing the pad around 6:30 pm. At long last, Starship SN6 began a smooth and fast flow that culminated in the ignition of Raptor SN29 around 7:45 pm, just 15 minutes before the end of SpaceX’s test window.
As with all SpaceX static fires, engineers must still analyze the data produced – and possibly inspect pad or rocket hardware – to verify vehicle health before proceeding into launch operations. Unlike all other SpaceX static fires, the company doesn’t announce the results of those tests – nor the solidified launch window – during prototype development programs. In the context of iterative aerospace development, while there may be such a thing as a “good” or “bad” test, all tests – as long as they’re performed safely and produce a large quantity of usable data – are essentially successful.
As such, it’s likely for the best that SpaceX doesn’t put the public focus on the “success” of any given test. Still, it means that unofficial educated guesses are typically the only way to determine the results of any given test and how those results impact the next steps. For SN6, the very broad-strokes conclusions one can draw from unofficial livestreams suggest that the Starship’s first Raptor static fire was a success. Assuming that the unknown cause(s) of the day’s two prior aborts were minor and easily rectified, SpaceX is likely exactly on schedule for Starship SN6’s first hop attempt.
SN6’s first flight is expected to be an almost identical copy of Starship SN5’s highly successful August 4th debut, following the same 150m (~500 ft) parabolic trajectory. Filed before SN6’s August 23rd static fire, SpaceX has penciled in Friday, August 28th for Starship SN6’s own hop debut. Thanks to the fact that SpaceX was able to complete both SN6’s cryo proof and static fire on the first day of their respective test windows, August 28th is likely well within reach. Stay tuned for updates as Starship SN6’s hop debut schedule solidifies.
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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.”
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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
