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SpaceX installs second Starship Mk1 canard ahead of transport to launch pad
SpaceX has begun to install Starship Mk1’s second of two forward ‘canards’, aerodynamic flaps the rocket prototype will soon use to attempt the first radical skydiver-style landing. SpaceX technicians are likely working to fully outfit the rocket before transporting its nose section to the launch pad, where it can be mated to Starship Mk1’s lower tank and engine section.
This second canard installation follows just a few days after SpaceX technicians began installing the first fin, a process that took a fair bit longer than usual as a result of new hardware integrated with the control surfaces this time around. Discussed earlier today, those large mechanism are likely the substantial actuators Starship will need to rapidly tweak its trajectory while falling through the atmosphere.
“Barely three weeks after the rocket’s forward flaps (canards) were removed, SpaceX technicians began the reinstallation process with one major visible difference: a massive motorcycle-sized actuator. The appearance of that previously unseen actuator mechanism on the first reinstalled canard suggests that this time around, SpaceX is installing Starship’s flaps with their final purpose of controlling Starship’s free-fall in mind.”
Teslarati, 11/04/2019
With the first installation complete, SpaceX’s Boca Chica technicians will likely be able to install Starship Mk1’s second canard more quickly. Beyond attaching the prototype’s control surfaces, SpaceX has also made a significant amount of progress outfitting Starship Mk1’s nose section with other hardware, notably fitting the nose’s exterior fuel lines with what is likely insulation.
That same black and silver insulation has been visible on SpaceX’s Starship Mk2 prototype in Cocoa, Florida, where technicians appear to have taken a slightly different step than Texas, insulating the plumbing before installing it on the vehicle.
Together again, at last
On October 30th, SpaceX lifted Starship Mk1’s tank and engine section onto a remote-controlled transported and moved the rocket half approximately a mile to its Boca Chica, Texas launch facilities, where Starship was installed on a freshly-constructed launch mount. SpaceX’s decision to move Mk1’s halves separately came as a bit of a surprise but appears to have been driven by a need to ensure that the spacecraft’s bottom half fit properly on the launch mount’s umbilical connections. Between the mount’s hefty steel beams, the beginnings of those panels (often deemed ‘quick disconnects’) are visible at the base of the panorama below.
Also visible around the base of Starship Mk1’s shiny aft section are a number of black steel structures – six, to be precise. Those protrusions are Starship’s landing legs, one of the last significant mechanisms installed on the rocket before SpaceX transported the half to the launch site. For unknown reasons, Starship Mk1’s legs – as well as Mk2’s – are almost nothing like those SpaceX have proposed for past Starship iterations and are even more dissimilar to Falcon 9’s extensively flight-proven hardware.
Instead of Falcon 9’s triangular, spread-eagle legs or BFR’s older tripod fin setup, Starship 2019 features six peg-like legs that only deploy or retract directly up or down. As some observers have noted, some of the hardware installed in and around those steel beam-like legs resembles industrial-grade linear brakes, suggesting that the legs will be deployed from their stowed positions by releasing those brakes and letting gravity do most of the work.
Layman concerns remain about the stability of six perfectly vertical legs with a span essentially the same as Starship’s own diameter, a possible indicator that the dead-simple landing legs on Mk1 and Mk2 may be dramatically simplified for the sake of speedy development. At the same time, it’s possible that their linear brake mechanisms could simultaneously offer some sort of minor suspension or terrain compensation, but their extremely narrow span fundamentally limits their potential stability. For landing on a prepared concrete slab, however, they will likely be sufficient, although almost any lateral velocity at all could result in Starship tipping over.
For now, SpaceX has road closures scheduled on November 7th, 8th, and 12th, the former two of which are probably more focused on transporting Starship Mk1’s nose section to the pad for installation atop the tank section. At the same time, SpaceX is clearly preparing for a series of major Starship tests, including a tank proof test, a wet dress rehearsal, and a triple-Raptor static fire. Stay tuned for updates!
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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
