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SpaceX tests Starship and Frankenstein ‘test tank’ simultaneously
After another few weeks of downtime, SpaceX has simultaneously tested the first orbital-class Starship prototype and a Frankenstein-esque ‘test tank’ at its South Texas facilities. While nothing that occurred was all that visually spectacular, the afternoon of testing was still noteworthy for a couple of reasons.
First up, following a successful six-engine Raptor static fire – the first in Starbase history – on November 12th, all signs pointed to Starship S20 attempting another static fire (its fourth) on December 1st. In the almost three weeks of inactivity between those planned tests, SpaceX likely performed extensive inspections of the pathfinder prototype and its Raptor engines. Technicians also repaired the minor heat shield damage and tile loss that testing incurred and patched a few other ‘holes’, effectively leaving Ship 20 with the first fully finished heat shield by the end of November.
Earlier this week, one of the few remaining Boca Chica Village residents received a safety notice from SpaceX indicating that a static fire test was scheduled on Wednesday, December 1st – followed soon after by a notice to mariners (NOTAM) warning boaters to keep to a safe distance. Two hours into the 10am to 6pm CST test window, Starship S20 was already venting and starting to get frosty, confirming that propellant loading had begun. A little over an hour later, it was clear that SpaceX had aborted the first static fire attempt of the day. For the next three hours, Ship 20 exhibited some unusual behavior including new vents, an apparent header tank pressurization or fill test, and still more odd venting in new places.
In the middle of Starship’s weird nose-related testing, SpaceX began simultaneously loading a new ‘test tank’ known as B2.1 with liquid nitrogen (LN2) – marking the first truly simultaneous test of multiple Starship test articles. As Ship 20 seemingly detanked for the second time that day, the B2.1 tank was fully loaded with LN2 and apparently pressure-tested not long after. A few hours later, the test tank was also detanked and the road to the pad was reopened, marking the end of the day’s testing.
Normally, nothing is particularly unusual or noteworthy about test tank testing. Since January 2020, SpaceX has routinely built and tested tanks that are effectively just shorter versions of actual tanks and hardware, using them to qualify changes to Starship’s design, materials, operations, and more before applying those changes to full-size prototypes. B2.1 is the tenth dedicated test tank to reach the launch pad in a little under two years.
Normally, the ‘B2.1’ name SpaceX has given the tank would imply that it’s a newer booster test tank (using Bx instead of BNx) following in the footsteps of BN2.1, which passed cryogenic and load testing this summer. Instead, though, B2.1 is a bit of a nightmarish amalgamation of seemingly random Starship and Super Heavy parts. Its forward dome is an old, unused booster section complete with the hexagonal structure grid fins would have been brace against. Its aft section is a booster thrust structure. Up to that point, it’s effectively just a copy of BN2.1.
However, SpaceX inexplicably installed a Starship thrust dome inside B2.1’s booster thrust structure, creating a test tank with no obvious relevance to any conceivable Starship or Super Heavy design or prototype. Further, SpaceX rolled B2.1 to the launch site for testing only after installing it on an unused device that’s believed to be the aft half of a dedicated booster structural test stand. In theory, a sort of ‘cap’ would be fitted on top of a booster or test tank installed in the stand’s base and strong cables would connect the two, allowing SpaceX to subject prototypes to compressive stress – like, perhaps, the forces a booster might experience while carrying a fully-fueled 1300-ton Starship to space. The upper half of that test structure has yet to be moved to the launch site.
Altogether, the weird half-complete test stand and bizarre fusion of ship and booster parts make B2.1’s purpose and initial testing a complete mystery. It’s unclear what value it provides that makes it more of a priority than, say, finally starting to test the first flightworthy Super Heavy booster (B4). Ultimately, the most interesting thing about B2.1’s test debut is the fact that it appears to mark the first use of Starbase’s brand new orbital tank farm, which is approaching completion.
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
