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SpaceX adds new ship to fleet after fairing catcher Ms. Tree nails second recovery in a row
In a telltale sign that SpaceX is growing much more confident in its ability to consistently recover Falcon 9 fairings, the company has accepted delivery of second recovery ship almost identical to GO Ms. Tree (formerly Mr. Steven) just days after nailing its second fairing catch in a row.
Previously known as M/V Captain Elliott, the new ship appears to have been acquired (or leased) by Guice Offshore (GO) from SEACOR Marine, who purchased Elliott from struggling marine services company Seatran Marine in 2017. One way or another, SpaceX now has a pair of Port Canaveral-based fairing recovery ships in hand – named Ms. Tree and Ms. Chief – and is thus making excellent progress towards catching and reusing both halves of the same Falcon 9 (or Heavy) fairing.
Splurging on ‘ships
Put simply, whoever is paying for or has paid for the two fast supply vessels (FSVs) that are now a part of SpaceX’s rocket recovery fleet has/had a tidy sum to spend. For ships as large, new, and high-performance as Ms. Tree and Ms. Chief, both completed in the mid-2010s, SpaceX or GO would be lucky to pay less than $10M apiece and each ship could easily cost more than $20M, depending on a variety of unknowns. Previous owner Seatran Marine is/was admittedly in dire financial straits, so that could have resulted in an effective fire-sale discount.
Regardless, this is to say that SpaceX was likely willing to splurge and open its wallet wide for extremely high-quality fairing recovery vessels because of just how expensive those fairings are. According to CEO Elon Musk circa 2017, it costs SpaceX $5-6M total to produce a set of Falcon fairing halves, equivalent to roughly 10% of the cost of a Falcon 9 launch ($50M-60M).
As an example, assume that SpaceX paid a full $50M for Ms. Tree and Ms. Chief – effectively a worst-case cost scenario. Assume that recovering and reusing net-caught Falcon fairings still costs half as much as building new fairings ($3M for two halves), also likely a worst-case scenario given the relative mechanical and propulsive simplicity of fairings.
In this mediocre-at-best scenario, it would still take SpaceX less than 20 launches with both halves recovered to completely recoup the cost of both fairing recovery ships. In the event that reusing caught fairings is only 25% as expensive as building new fairings, SpaceX could recoup its fleet investments in just 10 launches. In fact, cost reduction may even be a secondary consideration next to the potential for effectively doubling fairing production with the same facilities. From that perspective, spending, say, $50M on development and another $50M on cutting-edge recovery vessels could easily be a bargain, especially compared to the $1B+ SpaceX has spent deloping Falcon 9 booster reusability.
Fairing-catcher Mk4
With GO Ms. Chief’s August 10th arrival at Port Canaveral, SpaceX’s team of Florida-based recovery engineers and technicians will now be tasked with modifying the ship for Falcon fairing catching. SpaceX completed its first fairing recovery-focused modifications back in late 2017, likely producing what was the first version of fairing recovery tech (Mk1). The net proved to be far too small and was replaced in summer 2018 with a net and arms likely 4X larger (Mk2).
Roughly half a year and several missed catches after Mr. Steven’s Mk2 net was installed, the ship transited the Panama Canal and arrived at Port Canaveral in February 2019. Barely a week or two later, Mr. Steven suffered a failure at sea – well before a planned catch attempt – that saw the ship limp back to port missing the entirety of its net and two of four arms.
After another four months in port, SpaceX installed a third net and arms system on Mr. Steven, featuring distinct differences and apparent upgrades that likely make it Mk3. Shortly after installation and a quick renaming from Mr. Steven to GO Ms. Tree, Ms. Tree’s inaugural Mk3 recovery attempt culminated in SpaceX’s first and second successful fairing catches – back-to-back – on June 24th and August 6th.
Finally, this brings us to the blank slate that is GO Ms. Chief. Compared to Ms. Tree, both vessels are nearly identical: both are built by Gulf Craft, LLC, both are 205 ft x 34 ft (62m x 10m), both have decks rated for ~405 metric tons (900,000 lb), and have top speeds of 26-32 knots (30-37 mph, 50-60 km/h; fully-loaded vs. empty). The lone point of difference is power: Ms. Chief’s engines produce 500 more horsepower and its generators produce an additional 120 kW of power, respective improvements of 5% and 16% relative to Ms. Tree (Mr. Steven).
Despite both ships being nearly identical, SpaceX is unlikely to simply copy and paste Ms. Tree’s thus far successful arms and net, likely instead doing what the company is famous for and fabricating a new and improved variant of the fairing recovery mechanism. This would presumably translate to Mk4. Conveniently, SpaceX appears to be heading into a rare period of no launches, likely stretching almost three months from August 6th (AMOS-17) to late October.
If Mr. Steven and Ms. Tree’s transformations are anything to go by, that hefty chunk of time that should be more than sufficient to fully outfit Ms. Chief with a fresh fairing recovery mechanism, assuming SpaceX has been simultaneously fabricating the hardware in anticipation of Ms. Chief’s arrival.
For now, we’ll have to wait and see if SpaceX’s next launches – both believed to be 60-satellite Starlink missions – will mark the recovery debut of Ms. Chief, as well as the first attempted catch of both Falcon fairing halves. Additionally, following SpaceX’s second successful fairing half catch on August 6th, it’s possible that the company has two recovered halves capable of making a full, flight-proven fairing. Either way, a Starlink launch will likely support the flight-debut of a reused fairing and will almost certainly host the first attempted simultaneous recovery of both fairing halves.
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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.
Elon Musk
Judge clears path for Elon Musk’s OpenAI lawsuit to go before a jury
The decision maintains Musk’s claims that OpenAI’s shift toward a for-profit structure violated early assurances made to him as a co-founder.
A U.S. judge has ruled that Elon Musk’s lawsuit accusing OpenAI of abandoning its founding nonprofit mission can proceed to a jury trial.
The decision maintains Musk’s claims that OpenAI’s shift toward a for-profit structure violated early assurances made to him as a co-founder. These claims are directly opposed by OpenAI.
Judge says disputed facts warrant a trial
At a hearing in Oakland, U.S. District Judge Yvonne Gonzalez Rogers stated that there was “plenty of evidence” suggesting that OpenAI leaders had promised that the organization’s original nonprofit structure would be maintained. She ruled that those disputed facts should be evaluated by a jury at a trial in March rather than decided by the court at this stage, as noted in a Reuters report.
Musk helped co-found OpenAI in 2015 but left the organization in 2018. In his lawsuit, he argued that he contributed roughly $38 million, or about 60% of OpenAI’s early funding, based on assurances that the company would remain a nonprofit dedicated to the public benefit. He is seeking unspecified monetary damages tied to what he describes as “ill-gotten gains.”
OpenAI, however, has repeatedly rejected Musk’s allegations. The company has stated that Musk’s claims were baseless and part of a pattern of harassment.
Rivalries and Microsoft ties
The case unfolds against the backdrop of intensifying competition in generative artificial intelligence. Musk now runs xAI, whose Grok chatbot competes directly with OpenAI’s flagship ChatGPT. OpenAI has argued that Musk is a frustrated commercial rival who is simply attempting to slow down a market leader.
The lawsuit also names Microsoft as a defendant, citing its multibillion-dollar partnerships with OpenAI. Microsoft has urged the court to dismiss the claims against it, arguing there is no evidence it aided or abetted any alleged misconduct. Lawyers for OpenAI have also pushed for the case to be thrown out, claiming that Musk failed to show sufficient factual basis for claims such as fraud and breach of contract.
Judge Gonzalez Rogers, however, declined to end the case at this stage, noting that a jury would also need to consider whether Musk filed the lawsuit within the applicable statute of limitations. Still, the dispute between Elon Musk and OpenAI is now headed for a high-profile jury trial in the coming months.
Tesla’s Elon Musk: 10 billion miles needed for safe Unsupervised FSD
Tesla earns top honors at MotorTrend’s SDV Innovator Awards
