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SpaceX’s first flight-proven Starship could fly again, says Elon Musk
Elon Musk says that SpaceX wants to reuse its first flight-proven Starship prototype, although the rocket’s second hop might come after the debut of a totally different ship.
On August 4th, for the first time ever, a full-scale Starship prototype measuring some 9m (30 ft) wide and 30m (~100 ft) tall lifted off from SpaceX’s Boca Chica, Texas test facilities. Just three weeks shy of the first anniversary of Starhopper’s last flight test, Starship serial number 5 (SN5) essentially repeated the stubby prototype’s 150m (~500 ft) hop before (relatively) gently landing on an adjacent concrete pad.
Over the last several days, SpaceX has gradually been working through the unprecedented task of inspecting, safing, and relocating a flight-proven Starship. At the same time, the company has to check out the fixed launch mount structured that supported the test flight and provided Starship with power, propellant, and wired communications. As teams work to get both ship and mount ready for round two, CEO Elon Musk has taken to Twitter to discuss some of SpaceX’s nearer-term goals and plans for Starship testing – including SN5’s role in them.
Starship SN5’s hop debut was a spectacular success for SpaceX, verifying that steel and radically simple and manufacturing techniques can quickly build a cheap pressure vessel capable of controlled flight. The flight also reaffirmed that the next-generation Raptor engine is capable of operating uninterrupted for at least ~50 seconds, although Starhopper’s 150m hop proved the same thing some 20 engine prototypes and 13 months prior.
Still, while it unequivocally proved that SpaceX is on the right track, both the lead-up to Starship SN5’s hop and the hop itself hint that a few kinks will still need to be worked out. Notably, during SN5’s hop, part of Raptor engine SN27 appeared to catch fire at some point after ignition, producing substantial flames that lasted for at least 10 seconds. For any rocket engine, an onboard fire is always a possibility, but most engines are either designed to tolerate the inhospitable environment they create or heavily insulated from it.
Festooned with sensitive wires and harnesses, Raptor prototypes are likely not meant to experience an extended onboard fire and remain functional, but SN27 nevertheless did just that. At a minimum, Starship SN5 thus likely needs a new Raptor engine before it can begin to prepare for a second hop.
The prototype will also assuredly need several new landing legs after destroying at least two during its launch and landing debut. It’s worth pointing out that the leg damage visible above is almost certainly the result of an intentional design choice, ensuring that landings slightly rougher than expected transfer most of their stress into Starship’s legs instead of its hull. Given just how simple they appear, the current leg design likely makes them effectively disposable, allowing SpaceX to focus its effort on unsolved problems as a more refined and reusable leg design comes to fruition.
Aside from confirming that SpaceX at least intends to reuse Starship SN5 on future hops, Musk revealed that he wants to refine the launch procedure until the company is able to easily perform multiple Starship hops per day. This suggests that the next one or several months could be chock full of Starship hop attempts. Musk also noted that Starship SN6 – a prototype built along SN5 and effectively completed weeks ago – would likely attempt its first flight before SN5 hops a second time. SpaceX began stacking the upgraded Starship SN8 prototype just a few days ago, raising the question of whether Starship SN6 would be made redundant before it could even left the factory.
Thankfully, it seems that the ship will instead be able to work alongside its sister (SN5) to help SpaceX simplify and expedite Starship test and launch operations. As of now, it’s unclear when SpaceX intends to restart Starship testing, but Musk’s comments point towards the next test happening far sooner than later.
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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
