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SpaceX’s fleet of rocket recovery ships is about to get even bigger
Four months after SpaceX gave up on catching Falcon fairings and stripped and returned a pair of leased ships it had modified for that purpose, the company’s permanent fairing recovery solution has just come into focus.
The April 2021 departure of GO Ms Tree (formerly Mr. Steven) and GO Ms Chief from SpaceX’s East Coast fleet made it unambiguously clear that the company was abandoning fairing catching in favor of simply scooping the several million dollar nose cone halves off of the surface of the ocean. By the time that decision was made, SpaceX had reused fairing halves more than two dozen times on more than 15 Falcon 9 launches – practically none of which had actually been caught by Ms Tree or Ms Chief.
In fact, SpaceX had already begun to reuse ‘scooped’ fairing halves on commercial Falcon 9 launches, including two Transporter rideshare missions with dozens of different customers and SiriusXM’s SXM-7 multimillion-dollar geostationary communications satellite. Perhaps even more importantly, SpaceX was routinely flying splashdown fairing halves three or even four times and flew one particular half twice in just 49 days.
Put simply, thanks to the heroic and somewhat unexpected success of a small subset of SpaceX’s fairing recovery, waterproofing, design improvements, and refurbishment upgrades got so good even fairings that splashed down in the Atlantic Ocean could be rapidly reused and flown multiple (now 5+) times apiece. Onto its third consecutive year of only marginal success and a distinct lack of reliability, that meant that SpaceX’s long-struggling effort to catch Falcon fairings had effectively been made redundant.
While it’s likely that scooped fairing halves would never be certified to fly high-value US military or NASA payloads, SpaceX appears to have matured the technology to the point that it’s good enough for Starlink and many (if not most) of its private-sector launch customers. Along those lines, with Ms Tree and Ms Chief out of the picture by early April, SpaceX had to briefly shoehorn Dragon recovery ships GO Navigator and GO Searcher into scooping roles to continue recovering fairings and eventually decided to lease or rent two far larger ships with built-in deck cranes.
For whatever reason, those leases or rentals only lasted a handful of weeks apiece and the latest ship – Hos Briarwood – departed SpaceX’s fleet in early July. In an extremely rare impromptu hiatus, SpaceX hasn’t launched once since late June, likely explaining why Briarwood – with a 100% fairing recovery success rate over two missions – departed when it did.
Now, first reported by SpaceExplored.com, the first signs of SpaceX’s long-expected permanent fairing recovery solution have appeared at an obscure Louisiana drydock. By all appearances, for the first time in its history, SpaceX has outright purchased two decade-old offshore supply ships formerly known as Ingrid and Ella G. Thankfully, SpaceX wiped clean any hint of ambiguity with the installation of a classic SpaceX “X” and by renaming the ships “Bob” and “Doug” after the pair that became the first NASA astronauts to ride a Falcon 9 rocket and Crew Dragon spacecraft to orbit in May 2020.
Relative to any of SpaceX’s more permanent fleet, including ex-members Tree and Chief, Bob and Doug are massive ships, measuring more than 80m (260 feet) long. They’re also five or six times heavier than the likes of GO Searcher or Ms Tree. Aside from an obvious potential role as fairing ‘scoopers’ thanks to the installation of large deck cranes, Bob and Doug also appear to have had heavy-duty winches installed, implying that they could also double as drone ship towboats.
Potentially, that means that SpaceX could shrink the fleet of ships needed to support each drone ship booster landing from two to one, using Bog and Doug to both tow and service the landing platforms at sea.
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.
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
