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SpaceX Starship rocket could move to the launch pad today
SpaceX has finished stacking its fourth full-scale Starship prototype and public schedules show that the rocket could be moved to a nearby launch and test pad as early as April 20th.
Known as Starship serial number 4 (SN4), the rocket will be the third full-scale vehicle completed since the start of serial production, while Starship Mk1 – the first full-scale prototype – was built far more slowly and with different methods. Mk1 was destroyed during one of its first cryogenic liquid nitrogen ‘proof’ tests in November 2019, nearly nine months after assembly began in February. After Mk1’s failure, SpaceX spent about two months rapidly expanding and upgrading its Boca Chica, Texas Starship factory.
Around the end of January 2020, SpaceX kicked off the production of its first serial prototype – logically deemed SN1. Less than a month after its first steel rings were stacked and welded together, SpaceX transported the completed prototype to the launch pad. On February 28th, what CEO Elon Musk later described as a fault in its engine section “thrust puck” destroyed Starship SN1 during one of its first cryogenic proof tests. Barely a month later and after SN2 was modified into a “thrust puck” test tank and successfully tested, Starship SN3 rolled to the launch pad and was destroyed by operator and test design errors on April 3rd. Now, barely two weeks after SN3, Starship SN4 is about to begin testing.
By all appearances, work on Starship SN4 began around March 23rd, continuing a production schedule that has been consistently completing a full-scale rocket prototype every four or so weeks. While SpaceX has taken the unprecedented step of reusing a section of a prototype (SN3) destroyed during testing, every other aspect of the rocket is new and built more or less from scratch.
Just two days after Starship SN3’s salvaged skirt and SN4’s new engine section and aft liquid oxygen tank dome were stacked and welded together, SpaceX technicians attached a crane to the upper two-thirds of the rocket’s tank section and stacked it on top of the newly-finished engine section. 24 hours later, SpaceX teams have completed at least one circumferential seam weld, with a second soon to be finished.
Once that last weld is complete and passes inspections, Starship SN4 will be ready to be lifted onto a transporter and rolled down the road to SpaceX’s dedicated launch and test facilities. Of course, like SN3 and SN1 before it, SpaceX will likely still have a few days of work to get Starship SN4 ready for testing once it’s been moved to the pad.
Using Starship SN3’s timeline, Starship SN4 could be transported to the pad as early as April 19th or 20th and ready for testing by April 24th or 25th. This meshes well with a publicly-available road closure schedule, required because SpaceX often needs to close a public highway for certain Starship transport and testing operations. Per Cameron County’s website, SpaceX has a transport-related closure planned on April 20th. The first testing-related closure begins on Sunday, April 26th and lasts from 9am to midnight, with backups on Monday and Tuesday.
As always, delays should come as no surprise with prototype testing, and schedules are always fluid and liable to change at any second. Regardless, it looks like Starship SN4 is perhaps just a week from its first round of testing.
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
