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SpaceX aborts third Starship static fire attempt minutes before ignition
Perhaps just two or so minutes away from ignition, SpaceX Starship prototype SN9 aborted its third triple-Raptor static fire attempt late into the test window on January 12th
Already extended from 5 pm CST (UTC-6) to 8 pm CST, SpaceX only really started clearing the test facilities near the original end of the window and began loading its second fully-assembled Starship with liquid oxygen and methane propellant around 7 or 7:30 pm. At 7:58 pm, a local sheriff sounded a police siren to warn any local residents or workers of an imminent test – needed in the event of an explosion (“overpressure event”), which could turn shatter glass windows and pose a general hazard.
Now a well-worn, familiar process for unofficial Starship followers, the siren serves (however imprecisely) as an approximate T-10 minute marker for any kind of hazardous testing. Hoping to rectify two prior unsuccessful static fire attempts, Starship SN9 may have made it just 2-3 minutes away from a second ignition before an unknown issue caused SpaceX ground controllers or Starship itself to trigger an abort.
Rearing its head in the form of a large, simultaneous vent releasing pressure from Starship SN9’s methane and oxygen tanks, aborts are an equally familiar event for those that have followed along for the last year or two. Starships may have taken some spectacular leaps forward in 2020, but the program and the prototypes it is currently producing are still relatively immature and, in other words, not exactly refined, polished final products.
In 2020 alone, SpaceX destroyed Starship SN1 during pressure testing, toppled (and destroyed) SN3 with faulty test design, saw SN4 violently explode, and eventually flew Starships SN5, SN6, and SN8 – but not before multiple false-starts, aborts, and repairs. Through that hardware-rich process of trial and error, SpaceX managed to go from completing its first one-piece steel ring to the fully-assembled Starship SN8’s almost completely successful 12.5 km (7.8 mi) launch debut in twelve months.
While that sheer speed has been a huge boon for SpaceX, the company appears to have become more cautious in recent months with the introduction of the first full-height Starships – presumably each representing a more substantial investment and thus warranting additional risk-aversion. At the same time, Starship is clearly an extraordinarily complex launch vehicle and that complexity only grows as the program progresses, producing more and more complex prototypes that require equivalently complex testing.
Starship SN8 spent almost two months at the launch pad gradually completing several crucial tests before SpaceX ultimately cleared the rocket to attempt the program’s first high-altitude launch on December 11th. As of January 12th, Starship SN9 has been at the pad for three weeks. Meanwhile, Starship SN10 is practically ready to begin testing and SN11 could be made ready just a few weeks after that.
Starship SN9’s next (fourth) static fire attempt is now expected no earlier than Wednesday, January 13th, though that could quickly change depending on the severity of the problem that caused Tuesday’s abort.
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
