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SpaceX’s Elon Musk hints at “notable” Starship changes, explains static fire anomaly
CEO Elon Musk has offered an explanation for SpaceX’s recent Starship static fire anomaly and says that an overview of the next-generation rocket development program will be delayed to account for some “notable” design changes.
Over the last several months, Musk has promised to do one of his (thus far) usual annual Starship updates, either in the form of a presentation in South Texas, an article published on SpaceX’s website, or both. Originally expected in September or October, the CEO’s tentative schedules have come and gone several times. Simultaneously, however, SpaceX has been preparing Starship serial number 8 (SN8) for a range of crucial tests and Starship program firsts, recently culminating in a successful cryogenic proof test, multiple wet dress rehearsals (WDRs), nosecone installation, the first triple-Raptor static fire test, engine tests using smaller ‘header’ tanks, and more.
Unfortunately for SN8, the most recent Raptor engine header static fire – drawing propellant from two small internal tanks mainly used for landing burns – did not go according to plan, resulting in some kind of high-temperature fire and severing Starship’s hydraulic systems. For SpaceX test controllers, that meant a total loss of control of most vehicle valves and pressurization systems, essentially putting one of Starship SN8’s header tanks through an unplanned pressure and failsafe test. In the days since, what exactly caused that unfortunate failure has been the subject of a great deal of discussion – discussion that can finally be put to rest with new information from Musk himself.
In a surprise, SpaceX had apparently decided to add a failsafe to Starship SN8’s new nose section, installing what is known as a burst disk – effectively an automatic single-use valve. Once the upper (liquid oxygen) header tank reached dangerous pressures, the force of that pressure broke the seal, allowing the rocket to vent excess pressure and avoid what would have otherwise been a potentially catastrophic explosion.
The cause of that near-miss, according to Elon Musk, was as simple as debris kicked up during the Starship SN8 Raptor engine static fire directly prior. Producing up to 200 metric tons (~450,000 lbf) of thrust and an exhaust stream traveling some 3.3 kilometers per second (2 mi/s, Mach ~10), Musk says that Raptor tore apart a special ceramic coating covering the concrete directly beneath Starship SN8. Likely accelerated to extreme velocities in milliseconds, shards of that coating reportedly “severed [an] avionics cable, causing [a] bad [Raptor engine shutdown].”
Prior to Musk’s comments, SpaceX technicians had already removed on of SN8’s three Raptors – SN32 – on November 14th and replaced it with Raptor SN42 on November 16th, effectively confirming that any damage suffered by Starship’s engine section was easily repairable. It’s unclear how exactly a single severed cable could result in a Raptor engine seemingly dripping molten metal but regardless of the cause, the fix appears to have been a quick one.
In response to the anomaly, Musk says that Starship avionics cables will ultimately be routed inside steel pipes to shield them from debris, while “water-cooled steel pipes” will be added to the launch pad to help limit the damage Raptors can cause. Perhaps as a partial result of SN8’s troubles at the launch pad, Musk says that his Starship blog post will have to wait, as SpaceX “[may be] making some notable changes” to the launch vehicle.
Prior to Starship SN8’s failed November 12th Raptor test, SpaceX was expected to attempt three consecutive static fires before clearing the rocket for an ambitious 15 km (9.5 mi) flight test. One of those static fires had already been completed on November 10th and it’s unclear if SpaceX’s SN8 test plan has remained unchanged or if the static fire counter has been effectively reset. Either way, barring more surprises, there’s still a definite possibility that Starship SN8 will be ready for its launch debut by the end of November and an even better chance that it will launch some time between now and 2021. Stay tuned for updates!
Tesla’s Head of AI, Ashok Elluswamy, says that something that was expected with version 14.3 of the company’s Full Self-Driving platform has already partially shipped with the current build of version 14.2.
Tesla and CEO Elon Musk have teased on several occasions that reasoning will be a big piece of future Full Self-Driving builds, helping bring forth the “sentient” narrative that the company has pushed for these more advanced FSD versions.
Back in October on the Q3 Earnings Call, Musk said:
“With reasoning, it’s literally going to think about which parking spot to pick. It’ll drop you off at the entrance of the store, then go find a parking spot. It’s going to spot empty spots much better than a human. It’s going to use reasoning to solve things.”
Musk said in the same month:
“By v14.3, your car will feel like it is sentient.”
Amazingly, Tesla Full Self-Driving v14.2.2.2, which is the most recent iteration released, is very close to this sentient feeling. However, there are more things that need to be improved, and logic appears to be in the future plans to help with decision-making in general, alongside other refinements and features.
On Thursday evening, Elluswamy revealed that some of the reasoning features have already been rolled out, confirming that it has been added to navigation route changes during construction, as well as with parking options.
He added that “more and more reasoning will ship in Q1.”
🚨 Tesla’s Ashok Elluswamy reveals Nav decisions when encountering construction and parking options contain “some elements of reasoning”
More uses of reasoning will be shipped later this quarter, a big tidbit of info as we wait v14.3 https://t.co/jty8llgsKM
— TESLARATI (@Teslarati) January 9, 2026
Interestingly, parking improvements were hinted at being added in the initial rollout of v14.2 several months ago. These had not rolled out to vehicles quite yet, as they were listed under the future improvements portion of the release notes, but it appears things have already started to make their way to cars in a limited fashion.
Tesla Full Self-Driving v14.2 – Full Review, the Good and the Bad
As reasoning is more involved in more of the Full Self-Driving suite, it is likely we will see cars make better decisions in terms of routing and navigation, which is a big complaint of many owners (including me).
Additionally, the operation as a whole should be smoother and more comfortable to owners, which is hard to believe considering how good it is already. Nevertheless, there are absolutely improvements that need to be made before Tesla can introduce completely unsupervised FSD.
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.
Tesla AI Head says future FSD feature has already partially shipped
Tesla’s Elon Musk: 10 billion miles needed for safe Unsupervised FSD
