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Report: SpaceX to launch at least five back-to-back Crew Dragon missions for NASA
Update: Wasting no time at all, NASA has confirmed the Ars Technica report one day later, announcing that rookie astronauts Nicole Mann and Josh Cassada have been reassigned from Boeing Starliner missions to SpaceX’s Crew-5 Crew Dragon launch – currently no earlier than August 2022.
Ars Technica’s Eric Berger reports that NASA has begun the process of moving a number of astronauts assigned to Boeing’s ailing Starliner spacecraft to a SpaceX Crew Dragon mission scheduled no earlier than August 2022.
Per sources close to Berger, NASA has chosen to reassign two rookie astronauts to Crew Dragon as hopes of a crewed Starliner launch – and thus an opportunity for them to gain hands-on spaceflight experience – in the next 6-12 months continue to wither. Barring surprises, the implied change of plans behind those actions means that SpaceX now appears to be scheduled to fly five operational NASA Crew Dragon missions back to back before Boeing’s Starliner flies a single astronaut – let alone its first operational mission with four crew aboard.
In December 2019, nine months after Crew Dragon’s own uncrewed March 2019 debut, Starliner lifted off for the first time on a ULA Atlas V rocket. However, whereas Crew Dragon performed a practically flawless orbital launch, space station rendezvous, docking, departure, reentry, and splashdown on its first try, Starliner’s Orbital Flight Test (OFT) went horribly wrong as soon as it separated from Atlas V.
Due to shoddy prelaunch testing that failed to detect several gaping holes in Starliner’s software, the spacecraft effectively lost control as soon as it was under its own power. Aside from making ground communication and control far harder, Starliner burned through most of its propellant and pushed most of its maneuvering thrusters past their design limits in the first hour or two after launch. Due to the catastrophic software failure and lack of propellant margins, NASA unsurprisingly called off a planned space station rendezvous and docking attempt and Boeing ultimately ordered Starliner to reenter a few days after launch.
Mere hours before reentry, Boeing apparently detected and fixed another major software error at the last second, potentially preventing Starliner’s propulsion and service module from smashing into the capsule’s fragile heat shield and dooming the spacecraft to burn up during reentry. Ultimately, it’s likely that the only reason Boeing didn’t suffer a total loss of vehicle (LOV) during Starliner’s OFT debut spacecraft was dumb luck. Had the initial clock error been worse, Starliner could have failed to reach orbit entirely or burned through all of its propellant, resulting in an uncontrolled reentry. Had there been no clock issue, it’s hard to imagine that Boeing’s software team would have attempted the panicked, impromptu bug hunt that detected and fixed the service module recontact issue.
Now, 22 months after Starliner’s catastrophic OFT, Boeing has been forced to stand down from a second self-funded orbital flight test (OFT-2) due to the last-second discovery of more than a dozen malfunctioning valves on the second spacecraft’s service module. Aside from raising the question of how Boeing and NASA yet again failed to detect a glaring Starliner issue until the day of launch, Starliner’s valve issues appear likely to cause another multi-month delay as Boeing is forced to investigate the problem, find the root cause, and implement a fix on all impacted service modules.
NASA reassigning some of the astronauts scheduled to helm Starliner on its Crewed Flight Test (CFT) and first operational mission to Crew Dragon’s August 2022 Crew-5 launch seemingly implies that the space agency is not confident that Boeing will have completed Starliner OFT-2, passed extensive post-flight reviews, and readied another Starliner for CFT by Q3 2022. Given that NASA took some 14 months to OK Crew Dragon’s Demo-2 crewed flight test after Demo-1’s March 2019 success and a catastrophic April 2019 failure during a ground test of the recovered capsule, it’s not unreasonable to assume that NASA will take about a year after OFT-2 to approve Starliner’s first crewed flight test.
If significant issues arise during OFT-2, which is now unlikely to occur before early 2022, a year-long gap is even more likely. Ultimately, that means that there is now a significant chance that SpaceX’s Crew Dragon spacecraft will complete not just five – but six – back-to-back operational NASA astronaut launches before Starliner is ready for its first operational ferry mission. SpaceX, in other words, is now expected to singlehandedly hold the line and ensure biannual NASA access to and from the International Space Station (ISS) for more than two years despite charging NASA $2 billion less than Boeing (~$5B vs ~$3B) to develop Crew Dragon.
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
