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SpaceX Falcon 9 doubleheader still on track after fiery ULA launch abort
As previously reported by Teslarati, SpaceX announced intentions to launch two Falcon 9 missions from two Florida launchpads on Sunday, August 30th. However, the ambitious goal was left in limbo.
The record-breaking doubleheader was believed to hinge upon the Saturday morning launch of a United Launch Alliance (ULA) Delta IV Heavy rocket with a classified spy satellite. However, that is apparently no longer the case.
Instead of launching on time, ULA’s infrequently-flown heavy-lift rocket was hit by 72 hours of delays to rectify minor pad hardware bugs. Around 2 am EDT (UTC-4) on August 29th, Delta IV Heavy made it just seconds away from liftoff before the rocket’s autonomous flight computer detected an anomaly with pad hardware and aborted the launch. As a result, the three cores’ three Aerojet Rocketdyne RS-68A engines were forced to shut down after ignition – an uncommon Delta IV launch abort scenario that has historically required at least a week of work to recycle for another launch attempt.
ULA ultimately determined that it was not possible to recycle the countdown for another attempt although enough time remained in the launch window to do so. The launch vehicle was safed and a scrub was announced.
In a statement provided by ULA confirmed that the early shutdown was “due to an unexpected condition during the terminal count at approximately three seconds before liftoff.” ULA also confirmed that “the required recycle time prior to the next launch attempt is seven days minimum.”
ULA has to fly before SpaceX, right?
With a minimum of seven days required to recycle the ULA Delta IV Heavy for another launch attempt, it was unclear what that meant for the fate of the SpaceX SAOCOM-1B mission.
It was previously understood that in order for SpaceX to launch the SAOCOM-1B mission from nearby Space Launch Complex-40 (SLC-40), the ULA Delta IV Heavy would have to successfully launch first. The southern polar launch trajectory of the SAOCOM-1B’s mission is one that hasn’t been flown from Cape Canaveral, FL in nearly six decades. This particular flightpath includes launch hazard zones that inch ever so close to the launchpad of the Delta IV Heavy, which is currently still on its launchpad stacked with a classified payload for the U.S. government.
It was assumed that the Falcon 9 would suffer the same minimum delay of seven days, if not longer. However, on Saturday afternoon, August 29 a SpaceX media representative confirmed that the company was still targeting the historic double header launches on Sunday, August 30.
Double the launches, double the recoveries
If SpaceX can pull it off, Sunday is set to be a stellar day for Falcon 9 launches and landings. The SAOCOM-1B mission will feature a Return To Launch Site (RTLS) landing attempt of the expended Falcon 9 booster while the Starlink Falcon 9 booster is expected to land aboard the autonomous droneship “Of Course I Still Love You” currently stationed off the coast of South Carolina.
In an unusual move, SpaceX split up the fairing catching vessels. Initially, both vessels left Port Canaveral and headed south to a catch zone located between The Bahamas and Cuba in an attempt to catch both fairing halves of the SAOCOM-1B mission. Then, GO Ms.Tree did an about-turn and met up with the booster recovery vessels off the coast of South Carolina.
At the time of publishing, the two Sunday Falcon 9 launches are expected to occur just nine hours apart. The Starlink V1.0-L11 mission is slated to occur at 10:12am ET (1412 UTC) from Launch Complex 39-A at Kennedy Space Center while the SAOCOM-1B mission is set to launch at 7:18pm ET (2318 UTC) from SLC-40 at Cape Canaveral Air Force Station. As usual, SpaceX will host official launch webcasts live, typically beginning around 15 minutes before liftoff.
Check out Teslarati’s newsletters for prompt updates, on-the-ground perspectives, and unique glimpses of SpaceX’s rocket launch and recovery processes.
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
