News
SpaceX rocket ready for second reusability record, Starlink launch attempt
One of SpaceX’s first upgraded Falcon 9 Block 5 boosters is ready for its second attempt to set a reusability record after its March 15th Starlink launch attempt aborted at the very last second.
Now scheduled to send SpaceX’s sixth batch of 60 Starlink satellites into orbit no earlier than (NET) 8:16 am EDT (12:16 UTC), March 18th, the mission will be Falcon 9 booster B1048’s fifth. Just four months ago, the booster successfully launched the first 60 upgraded Starlink v1.0 satellites, also becoming the second SpaceX rocket to fly four times. While B1049 – B1048’s predecessor – was first to reach the four-flight milestone in May 2019, B1048 is now on track to take the next leap forward for Falcon 9 reusability.
First noted shortly after the abort on SpaceX’s March 15th launch webcast, the company later clarified that what could have been attributed to hardware failure was likely just an issue with software or sensors. Milliseconds before liftoff, Falcon 9’s autonomous flight computer seemingly didn’t like what it saw while interpreting the telemetry flowing in from the ignition of B1048’s nine Merlin 1D engines. Whatever the specific trouble, Falcon 9 believed that one or several of those Merlin 1D engines were producing more thrust than they should.
While likely oversimplifying what is a spectacularly complex logic system, the flight computers that control Falcon launch vehicles from T-1 minute to mission completion have to treat the messy uncertainty of reality through a black and white lens. Lacking the ability to heuristically interpret the data they process, the computers instead rely on algorithms that filter thousands of channels of telemetry into a handful of simple categories. If that data aligns with the computer’s expectations, things are okay. If the data doesn’t agree with the plan, things are not okay. There are, of course, many more levels of complexity, but the concept of operations remains mostly the same.
However, the telemetry itself is also a potential point of failure – bad data could lead the flight computer astray, concluding that things are okay when they aren’t or vice versa. To handle that potential failure mode, SpaceX relies on multiple strings of telemetry (and even multiple computers), all gathering and analyzing the same things simultaneously. If one of several redundant sensors starts to disagree with its brethren, reporting different data back to Falcon 9’s flight computers, it’s apparent that the sensor – not the thing it’s measuring – is likely at fault. Still, out of an abundance of caution, SpaceX avionics typically treat most “out-of-family” sensor readings as reason enough to delay or fully abort a launch. When a launch delay can be little more than an annoyance with a negligible cost, it’s almost universally better to be safe than sorry.
With Falcon 9 B1048’s March 15th false start, the rocket’s computer appears to have received conflicting readings from the same family (or families) of engine thrust sensors. While, as noted above, the fault almost certainly lay in an engine sensor or two and not in the engines themselves, the flight computer chose caution over expedience and halted the launch milliseconds before it would have otherwise commanded clamp release and lifted off.
Confirmed by SpaceX delaying the Starlink V1 L5 mission by just three days, the issue was almost certainly software or sensor-related. Given that SpaceX continues to push the envelope of launch vehicle reusability, it’s honestly more surprising that aborts like these aren’t more common. Instead, the reality is that Falcon 9 Block 5 – aside from delays from the occasional upper stage fault – almost never suffers hardware-related aborts when compared to the rocket’s prior iterations.
Featuring the second-ever flight-proven Falcon payload fairing, Falcon 9 B1048 will hopefully become the first SpaceX rocket to complete five orbital-class launches and landings. With more than a little luck, there’s also a smaller chance that the mission could mark the first time SpaceX successfully catches both fairing halves with twin ships Ms. Tree and Ms. Chief.
Tune in for SpaceX’s second Starlink V1 L5 launch attempt around 8am EDT (12:00 UTC) to catch the potentially record-breaking launch and landing live.
Check out Teslarati’s Marketplace! We offer Tesla accessories, including for the Tesla Cybertruck and Tesla Model 3.
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.”
News
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
