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SpaceX rapidly stacks Starship and Super Heavy with ‘Mechazilla’
For the second time ever, SpaceX has used Starbase’s ‘Mechazilla’ tower and arms to stack a Starship upper stage on top of a Super Heavy booster.
This time around, though, SpaceX clearly learned a great deal from its second February 9th Starship stack and was able to complete the stacking process several times faster on March 15th. During the second attempt, depending on how one measures it, it took SpaceX around three and a half hours from the start of the lift to Starship fully resting on Super Heavy. With Stack #3, however, SpaceX was able to lift, translate, lower, and attach Starship to Super Heavy in just over an hour.
Oddly, SpaceX managed that feat without a claw-like device meant to grab and stabilize Super Heavy during stacking operations. For Stack #2, all three arms were fully in play. First, a pair of ‘chopsticks’ – giant arms meant to grab, lift, and even recover Starships and boosters – grabbed Ship 20, lifted it close to 100 meters (~300 ft) above the ground, rotated it over top of Super Heavy, and briefly paused. A third arm – known as the ship quick-disconnect or umbilical arm – swung in and extended its ‘claw’ to grab onto hardpoints located near the top of Super Heavy. Once the booster was secured, the ‘chopsticks’ slowly lowered Ship 20 onto Booster 4’s interstage and six clamps joined the two stages together.
A few hours after the two were clamped together, an umbilical device located on the swing arm extended and connected to Ship 20. It’s unclear if the panel was actually used in any way but the umbilical is designed to connect Starship to ground systems to supply propellant, power, communications, and other consumables. Regardless, the device did appear to connect to Starship. Prior to Stack #3, however, SpaceX removed both of the swing arm’s ‘claws,’ meaning that it had no way to grab onto Super Heavy. That diminished capability clearly appeared to have zero impact on the ease or speed of the stacking process given that it was completed a full three times faster than Stack #2.
That could imply that the claw is either completely unnecessary or only needed when attempting stacking operations in extreme winds. What is clear is that the claw removal likely only shaved a handful of minutes off of the full stacking process. What really saved time on Stack #3 was a faster lift and fewer pauses throughout – especially while lowering Starship the last several meters onto Super Heavy. During Stack #2, SpaceX took close to an hour and a half to fully lower Ship 20. The same sequence took just ~20 minutes during Stack #3.
Still, after the impressively rapid one-hour stack, it then took SpaceX close to two hours to connect the swing arm’s umbilical to Starship, leaving plenty of room for improvement. Ultimately, assuming SpaceX can speed up the start of the stacking process and replicate its Starship success with Super Heavy, which will also need to be grabbed and installed on an even more complex launch mount, it’s possible that Starbase’s orbital launch integration system is already capable of supporting multiple Starship launches per day. Of course, SpaceX has yet to demonstrate that the orbital launch site can be turned around in a matter of hours after being subjected to the violence and stresses of a Starship launch.
More significantly, SpaceX has never even attempted an orbital Starship launch, recovery, or reuse. That leaves the company in the unusual position of building and testing expensive, specialized support equipment before it actually knows that the rocket that equipment is designed to support is in any way capable of taking advantage of it. For an orbital spacecraft the size of Starship, only the Space Shuttle comes anywhere close and NASA’s all-time record for orbiter turnaround was 54 days. SpaceX has technically flown two Falcon 9 boosters twice in 27 days but no matter how impressive that feat is, reusing a far smaller suborbital booster is vastly easier than reusing a massive orbital spacecraft.
At the end of the day, it’s not really SpaceX’s fault that it’s still waiting for permission to attempt orbital test flights. Nonetheless, the growing gap in maturity between Starship and Super Heavy and the orbital launch site designed to support them continuously raises the risk that SpaceX will have to extensively redesign the rocket, its support equipment, or both if significant problems arise during orbital test flights.
Up next, there’s a chance that SpaceX could attempt to cryoproof Starship while on top of Super Heavy – or perhaps both stages at once. While SpaceX has performed more than half a dozen cryoproofs of Ship 20 and Booster 4 using the orbital launch site’s propellant storage and distribution system, it hasn’t fully tested the hardware needed to route hundreds of tons of propellant hundreds of feet into the air – essential for full-stack testing and launch operations.
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
