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SpaceX installs Starship booster on orbital launch mount for the third time
After several signs of imminent activity on Sunday, SpaceX has installed Super Heavy Booster 4 (B4) on Starbase’s lone ‘orbital launch mount’ for the third time.
Around 10am CST (UTC-6), SpaceX began retracting more than a dozen clamps that hold the 69m (~225 ft) tall Super Heavy – the largest booster ever built – to its transport and work stand. By 11:30am, Booster 4 was safely extracted from the stand and hovering above it as the lift team crossed their Ts and dotted their Is before proceeding. SpaceX’s newest Starbase crane then spun around and crawled a short distance to the orbital launch mount, where it lifted Booster 4 above the mount.
In a process that this particular Super Heavy prototype is thoroughly familiar with, SpaceX then very carefully lowered B4 down into the center of the donut-shaped orbital launch mount, where 20 separate clamps – each capable of deploying and retracting – form a support ring and giant hold-down clamp.
It’s unclear how exactly that process of mount installation works but it could be quite the orchestration. By all appearances, Super Heavy hold-down clamps – mechanical devices designed to hold the booster to its work stand or keep it immobile on the launch mount during a variety of test – work by reaching inside the lip of the booster’s aft ‘skirt,’ which sports a very sturdy ring of steel that 20 Raptor Boost engines mount to and push against. The 20 clamps fit precisely between each of those 20 outer Raptors and grab onto Super Heavy from the inside.
Just before liftoff, all 20 hold-down clamps will rapidly retract back into the orbital launch mount. So will another 20 small quick-disconnect umbilical panels designed to supply every single Raptor Boost engine with the gases they need to ignite. The primary booster quick-disconnect – which connects Super Heavy to power, communications, and propellant supplies – will also retract into a hooded enclosure at some point during the process. Finally, a giant, swinging arm located about halfway up Starbase’s ‘launch tower’ will retract a similar quick-disconnect panel for Starship fueling, retract two claw-like support arms, and swing back for liftoff.
Altogether, while there are likely even more than just those described above, a single Starship launch will require at least 44 separate devices to successful actuate in rapid and precise succession – 41 for Super Heavy and at least 3 for Starship. That incredible complexity – probably making Starship’s the most mechanically complex launch mount in the history of rocketry – may partially explain why Super Heavy Booster 4 has yet to even attempt a single proof test more than four months after it first left the high bay it was built in.
Without a functioning orbital launch mount, it hasn’t been possible to fully test a Super Heavy booster. With any luck, on their third rendezvous, both Booster 4 and the orbital launch mount are finally close enough to completion to perform some serious testing. At the absolute minimum, everything appears to be in order for SpaceX to properly connect Super Heavy to the launch mount and pad for the first time – the process of which is already underway. Aside from connecting B4 to the mount’s hold-down clamps, which has been done twice before, SpaceX can now attach all 20 Raptor quick-disconnects and the main booster quick-disconnect to a Super Heavy for the first time. Further up the tower, SpaceX can also partially test out the Starship quick-disconnect arm, which is half-designed to grab onto and stabilize Super Heavy.
SpaceX currently has road closures (signifying plans for ship, booster, or pad testing) scheduled on Tuesday through Friday this week, hinting at the possibility that Super Heavy B4 could finally start proof testing in mid-December.
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
