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SpaceX stress-tests Starship-catching arms with giant water balloons
SpaceX has begun testing Starbase’s rocket-catching arms with ballast to simulate the weight of Starship and Super Heavy.
SpaceX started the process of proof testing those arms about a week ago, beginning with some basic calibration work. Together, the three arms and launch tower amount to a giant custom-built robot that SpaceX CEO Elon Musk has deemed “Mechazilla.” Controlled with a complex system of hydraulic and electromechanical actuators spread throughout each structure, SpaceX must calibrate all of those devices to enable the full range of motion the arms are meant to be capable of. To do so, SpaceX appeared to actuate both catch arms (also known as “chopsticks”) as far as they were able to move on January 4th, producing data that could be fed back into the system’s control software to properly set limits of motion.
A handful of days later, arm testing continued, with SpaceX lifting the carriage higher than it had traveled before and demonstrating more complex longitudinal movements that required synchronized motion of both arms. On January 9th, SpaceX performed the most ambitious arm testing yet, nearly lifting the arms to the top of their ~140 meter (~460 ft) tall launch tower backbone to simulate the range of vertical motion required to lift and stack Starship and Super Heavy.
SpaceX also installed a temporary frame meant to simulate a Starship or Super Heavy booster, foreshadowing additional testing planned in the coming days. That jig upped the stakes for the longitudinal actuation portion of January 9th’s testing, as anything less than the precise, synchronized movement of both arms could have caused the heavy steel frame to fall hundreds of feet onto a range of equipment and structures directly below it. Thankfully, the arms performed well and returned to their resting position without issue.
On January 11th, SpaceX proceeded to install six ‘water bags’ – three to a side – on the Starship simulator frame. Amounting to giant, heavy-duty water balloons, those bags are routinely used to stress-test large structures and devices by simulating payloads that might be too expensive or inconvenient to use solely for testing purposes. With those seemingly empty bags attached, SpaceX proceeded to move the catch arms up and down the full length of the launch tower at record speed, taking about seven minutes to climb and descend ~120 meters (~400 ft) – averaging a brisk 0.6 mph or 1 km/h.
Here is a video from Giga Texas of this type of mass simulator! pic.twitter.com/uHfah45WVt— Zack Golden (@CSI_Starbase) January 11, 2022
On January 12th, SpaceX filled the balls with water, producing some… interesting… visuals. Ridiculous appearances aside, the six bags SpaceX chose to use could be 20, 35, or 50-ton variants, meaning that all six could weigh anywhere from 120 to 300 tons (264,000-660,000 lb) if fully filled. In other words, perfect for simulating the dry masses of Starship (roughly 80-120 tons) and Super Heavy (150-200+ tons).
SpaceX did appear to fully fill around four of the six bags and partially filled the other two, causing the whole arm structure to visibly sag during the fill process as the weight of the ballast stretched the several-inch-thick steel cable holding the whole device aloft. In the late afternoon, the laden arms lifted around 10-20 meters and rotated left and right, partially demonstrating the process of rotating a lifted Starship or Super Heavy into position for stacking or launch mount installation. They were never lifted high enough to truly demonstrate that ability, though, and were lowered back to the ground soon after.
As of 10pm CST, January 12th, the water bags appear to have been fully drained after their first excursion. It’s likely that load-testing will continue over the next several days or weeks – SpaceX may just want to avoid leaving the arms fully loaded overnight.
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
