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SpaceX schedules second Starship static fire after first test ends prematurely
Update: SpaceX appears to have plans for a second triple-Raptor static fire for Starship SN9 after the rocket’s first test was cut short for unknown reasons.
Identical to previous road closure windows, SpaceX will have an opportunity to test Starship SN9 from 8 am to 5 pm CST (UTC-6) on Friday, January 8th, potentially paving the way for a high-altitude launch attempt early next week if the second static fire goes as planned. Stay tuned for updates!
In what is likely one of the last steps before SpaceX’s next high-altitude Starship launch attempt, the company appeared to successfully put Starship serial number 9 (SN9) through its first triple-Raptor static fire test.
Relatively late into a test window that opened at 8 am CST (UTC-6) but was later pushed to noon, SpaceX’s first Starship SN9 static fire attempt began in earnest around 3:15 pm CST. Signified by venting activity at the propellant farm tasked with preparing and loading liquid oxygen and methane on Starships, slight tweaks in the test flow were observed but the static fire occurred more or less when expected at 4:07 pm.
SN9 ignited all three of its Raptors in quick succession and shut the engines down over the course of 1.5-2 seconds – extremely short relative to all previous nominal Starhopper or Starship-mounted Raptor static fires. Long-time followers immediately noted that small discrepancy, speculating that it could either have been a post-ignition abort or intentionally shortened to avoid damaging the pad’s concrete surface (an incident that’s occurred several times during recent tests).
Not long before the short static fire, SpaceX extended the end of its January 6th test window (in the form of road closure notices) from 5 pm to 8 pm. Oddly, rather than the expected response of detanking Starship and reopening the road after a successful test, SpaceX essentially recycled SN9 and began a separate test around 6 pm. The road was never reopened and a SpaceX team never headed back to the pad between the tests, implying that the company may have run into a minor hardware or software bug earlier in the day.
It’s unclear what the actual goal of the second attempt was and it’s more or less impossible to know for sure with confirmation from CEO Elon Musk. It’s possible – if unlikely – that the first static fire went exactly as planned and the follow-up test was meant to be a simple data-gathering wet dress rehearsal (WDR). Either way, after a surprise downpour briefly engulfed Starship SN9 minutes prior, the second test appeared to abort about 30 minutes into propellant conditioning and loading, precluding both a complete WDR and/or static fire.
According to a test notice received on January 6th by NASASpaceflight contributer and photographer Mary (bocachicagal), SpaceX has another test window available on January 7th in the event that Wednesday’s testing was partially unsuccessful. In a rare case, SpaceX’s hand-distributed warning for residents preceded any additional planned road closures, the last of which lifted on January 6th.
On January 5th, SpaceX received a trio of Temporary Flight Restrictions (TFRs) from the FAA that will allow the company to restrict access to nearby airspace for high-altitude Starship launch attempts on January 8th, 9th, and 10th. Lacking an unequivocally successful static fire, it’s highly unlikely – but not impossible – that Starship will be ready for a launch attempt during any of those three windows. Still, it’s safe to say that SN9 is probably less than a week away from its first flight – expected to be a carbon copy of SN8’s 12.5 km (7.8 mi) launch and landing attempt – if SpaceX can complete a full-duration static fire in the next day or two.
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
