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SpaceX's in-flight rocket engine failure threatens NASA astronaut launch debut
An in-flight rocket engine failure during SpaceX’s March 18th Starlink launch could pose a threat to the company’s imminent NASA astronaut launch debut according to a statement provided by the space agency yesterday.
SpaceX and NASA are currently working around the clock to prepare a Falcon 9 rocket and Crew Dragon spacecraft for the company’s inaugural astronaut launch, a flight known as Demonstration Mission 2 (Demo-2/DM-2). All launch vehicle and spacecraft hardware – including booster B1058, an expendable upper stage, a spacecraft trunk, and the Crew Dragon capsule itself – are already believed to be at SpaceX’s Florida launch and processing facilities.
Prior to March 18th, the biggest gating items were believed to be a few final parachute tests and a whole lot of paperwork and reviews, as well as some important but less showstopping astronaut training. Unfortunately, SpaceX has suffered two unforeseen issues of varying severity in the last few days, both of which are now all but guaranteed to impact Crew Dragon’s astronaut launch debut schedule.
“According to the CCtCap contracts, SpaceX is required to make available to NASA all data and resulting reports. SpaceX, with NASA’s concurrence, would need to implement any corrective actions found during the investigation related to its commercial crew work prior to its flight test with astronauts to the International Space Station. NASA and SpaceX are holding the current mid-to-late May launch timeframe, and would adjust the date based on review of the data, if appropriate.”
NASA — March 25th, 2020
On March 18th, less than three minutes after liftoff and shortly before stage separation was scheduled, Falcon 9 booster B1048 – on its historic fifth launch attempt – suffered an engine failure visible on SpaceX’s official webcast. By all appearances, Falcon 9’s autonomous flight computer accounted for the engine’s failure, shutdown, and the resultant loss of thrust by burning B1048’s eight remaining engines for several seconds longer than planned.
While that extra few seconds of burn time likely ensured that the rocket’s upper stage was able to make it to the correct orbit after stage separation, roughly five minutes after B1048’s extremely rapid engine failure, contact was lost. For the first time ever, there were no landing burn-related call-outs from SpaceX launch operators, the first sign that something was seriously wrong. A few minutes later, SpaceX’s webcast hosts acknowledged that the booster had been lost, perhaps lacking the propellant it needed to attempt a landing.
For reference, Merlin 1D engines likely consume some ~270 kg (600 lb) of fuel each second. Falcon 9’s landing propellant reserves are believed to be on the order of 50+ metric tons (110,000 lb). Excluding the failed engine, eight Merlin 1Ds burning at full thrust for an additional 5 seconds would consume 20% of the propellant needed for landing; 10 seconds and it would use 40%.
The anomaly was Merlin 1D engine’s first in-flight failure ever. The 2012 failure of one of an original Falcon 9 V1.0’s rocket’s nine Merlin 1C engines is SpaceX’s only other in-flight failure.
It’s likely that B1048’s engine failure was primarily related to the fact that the booster was SpaceX’s pathfinder for a fifth-flight reusability milestone, making it the most reused rocket booster ever launched. NASA currently requires all of its Crew Dragon missions to launch on new Falcon 9 rockets, hopefully mitigating direct corollaries between the Starlink L6 anomaly and astronaut launches. Regardless, the space agency says that the company will now have to complete its internal failure review and implement necessary hardware, software, or rule changes before it’s allowed to launch NASA astronauts.
That investigation could take a matter of weeks, possibly even less, but it’s entirely possible that it could take months – let alone fixing the problems that allowed the in-flight Merlin 1D engine failure to happen in the first place. Ultimately, it will almost certainly make even the first flights of Falcon 9 and Heavy rocket boosters safer, but it could substantially delay SpaceX’s Demo-2 astronaut launch debut. Still targeted no earlier than (NET) mid-to-late May 2020, it’s safe to say that it’s reasonable to expect that schedule to slip over the next 4-6 weeks. 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
