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SpaceX Super Heavy booster assembly to start “this week,” says Elon Musk
CEO Elon Musk says that SpaceX is on track to begin fabricating Starship’s first Super Heavy booster prototype later “this week” and even revealed plans to hop that booster in the very near future.
Taller than an entire two-stage Falcon 9 or Falcon Heavy rocket, Super Heavy will be the largest and most powerful liquid rocket booster ever built by a factor of two (or more). Measuring ~70m (~230 ft) tall, Super Heavy will weigh at least 3500 metric tons (7.7 million lb) when fully loaded with liquid oxygen and methane propellant. According to Musk, SpaceX’s thrust target for the booster is 7500 tons (~16.5 million lbf) – significantly more than twice the thrust of the Saturn V and Soviet N-1 rockets and more than three times the thrust of SpaceX’s own Falcon Heavy.
On paper, while multiple times larger and more powerful, Super Heavy will be substantially simpler than Falcon Heavy thanks to its single-core. Built out of the same simple steel rings used to assemble Starship prototypes, Super Heavy should also be substantially cheaper to build than Falcon Heavy. Thanks to the experience SpaceX has already gained through months of Starship production, testing, and iterative improvement, initial Super Heavy prototype production could have a much smoother start, but several major challenges remain.
SpaceX has structured its Starship development program in such a way that the hardest technical challenges are generally first in line. Raptor engine testing came first in September 2016, although SpaceX did simultaneously build and test a full-scale carbon composite liquid oxygen – a material choice that was ultimately made redundant by the move to steel in late 2018. Up next, Starhopper served as a sort of proof of concept for the assembly of a flightworthy steel rocket in an unprotected open-air tent.
Starship Mk1 came next and was built as a full-scale prototype in similarly spartan conditions – but with much thinner steel. Mk1 ultimately failed prematurely, serving as a catalyst for SpaceX to substantially upgrade its South Texas rocket production capabilities, as well as its manufacturing techniques. Beginning in January 2020, SpaceX completed a rapid-fire series of tests with three stout tank prototypes and five full-scale Starship tank sections over the next seven months, passing multiple challenging pressure tests, wet dress rehearsals, Raptor static fires, and even a 150m (500 ft) hop.
The biggest challenges still facing Starship (5+ minute Raptor burns, skydiver-style landings, heat shield qualification, orbital launch/reentry/reuse) are mostly unique to the orbital spacecraft. In other words, with all SpaceX has already accomplished so far with Starship development, it could very well be ready to build a fully-capable Super Heavy prototype right now.
Along those lines, Musk says that there’s a chance that SpaceX will be ready to hop a Super Heavy booster prototype as early as October 2020 – less than two months after the first prototype enters production. Musk also noted that the biggest technical challenge facing Super Heavy is its extraordinarily complex ‘thrust puck’ – a metal structure that must host up to 28 Raptor engines and transfer all of their thrust through the rest of the rocket.
Per past comments, SpaceX will begin booster testing – possibly up to and including the first few orbital launch attempts – with as few Raptor engines as possible. For Musk’s aforementioned booster hop test, Super Heavy could reportedly hop with as few as two Raptors installed. Beyond those early tests and Super Heavy thrust puck development, perhaps only other challenge facing SpaceX is finalizing Raptor’s design to the point that dozens of engines can be built in short order. As of now, SpaceX has completed 40 Raptor prototypes in 18 months, while every Starship/Super Heavy pair will need as many as 34 engines apiece.
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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.”
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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
