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SpaceX recovery ships head to sea for first 'whole-fairing' catch attempt
After a brisk day-long cruise into the Atlantic Ocean, SpaceX’s twin Falcon fairing recovery ships have reached the general landing area to prepare for their first true ‘whole-fairing’ catch attempt.
Formerly known as Mr. Steven, GO Ms. Tree and new sister ship GO Ms. Chief departed Port Canaveral on December 14th and arrived at their designated recovery roughly 36 hours later. Now stationed just shy of 800 km (500 mi) downrange of SpaceX’s LC-40 Cape Canaveral Air Force Station (CCAFS) launch site, the ships are in position and can begin to prepare for Falcon 9’s Kacific-1/JCSAT-18 launch.
Scheduled to lift off no earlier than (NET) 7:10 pm ET, December 16th (00:10 UTC, Dec 17), Falcon 9 will place the ~6800 kg (15,000 lb) Kacific-1/JCSAT-18 communications satellite in a geostationary transfer orbit (GTO). Falcon 9 booster B1056 will attempt its third landing around nine minutes after launch, to be followed 25 minutes later by satellite deployment from the rocket’s upper stage. deploying the satellite around thirty minutes after launch.
If all goes according to plan, another 12-15 minutes after Falcon 9’s second stage (S2) deploys the Kacific-1/JCSAT-18 satellite, the rocket’s payload fairing halves will begin their final approach towards recovery ships Ms. Tree and Ms. Chief. Just shy of identical twins, the two ships have been outfitted with custom arms, boom supports, and nets with the intention of quite literally catching payload fairing halves out of the air after orbital Falcon 9 (and Heavy) launches.
SpaceX’s fairing recovery development program has had a long and arduous journey from Mr. Steven’s (now Ms. Tree’s) arrival at the company’s Port of Los Angeles dock space (late-2017) to the ship’s first attempted fairing catch (February 2018) and first successful catch (June 2019). In the 20+ months SpaceX has been attempting fairing recoveries, at least a dozen intentional soft ocean landings and seven net catches have been attempted, with numerous successful splashdowns and recoveries ultimately followed by two consecutive catches in June and August 2019.
The fact that SpaceX consecutively caught two fairing halves a little over two months apart after five failed catch attempts suggests that the company has effectively solved the majority of the fairing recovery challenge, becoming the first company (or space agency) in the world to do so. Unfortunately, a three-month launch lull after the second successful catch precluded any rapid-fire follow-up attempts and when that lull came to an end on November 11th, Ms. Tree and Ms. Chief were both ready but were forced to abort the attempt by rough seas.
Both ships actually spent several weeks docked (or stranded) in a North Carolina port after that aborted mission, potentially indicating that SpaceX had to fly a team north to inspect both ships’ arms and ensure that they could make the journey back to Port Canaveral. They were ultimately cleared and returned to their home port around ten days later, where their arms and booms were immediately removed. It’s unclear why that removal occurred but SpaceX’s recovery team rapidly reinstalled their arms in just a few days, followed by their nets soon after.
Given that their first simultaneous (i.e. ‘whole-fairing’) catch attempt was aborted before it could start, it’s safe to say that December 16th’s hopeful attempt will be Ms. Tree’s and Ms. Chief’s first side-by-side recovery mission. Both ships have successfully reached the recovery zone, a step further than they managed to get on their November attempt. Coincidentally, that November launch happened to mark both SpaceX’s and the world’s first launch of a flight-proven payload fairing, both halves of which were recovered from the ocean and represented a more or less worst-case scenario for reuse.
And nevertheless, that reuse was a flawless success, marred only by the fact that Ms. Tree and Ms. Chief were unable to attempt to recover the world’s first twice-flown payload fairing. In short, all the conditions are right for what could be the world’s first successful recovery of both halves of an orbital-class payload fairing. If successful, SpaceX will have effectively closed the book on Falcon 9 and Heavy reusability development, having proven that both boosters and fairings can be reliably and routinely recovered and reused.
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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
