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SpaceX reinstalling 29 Raptor engines on first orbital-class Starship booster
For the second time this month, SpaceX has begun installing 29 Raptor engines on Starship’s first orbital-class Super Heavy booster, potentially paving the way for several crucial milestones.
On August 1st, around the same time as SpaceX finished installing car-sized grid fins on a Super Heavy for the first time, the company began the process of installing multiple Raptor engines on the booster (#4) that might one day support Starship’s first orbital launch attempt. Not long after it began, it became clear that SpaceX was installing a full 29 Raptor engines on Booster 4 (B4) at a breakneck pace, and less than 24 hours later, all had been attached to Super Heavy’s thrust structure.
Barely a day later, Super Heavy Booster 4 was rolled to the orbital launch pad and installed on a massive ‘launch table’ that was itself installed just a few days prior after months of assembly. Four days after engine installation, Starship S20 and Booster 4 were briefly mated together, forming a full Starship stack – the tallest and most powerful rocket ever built – for about an hour. However, while it did serve as a useful learning experience and pathfinder operation, both stages were demated and returned to the factory soon after.
Since Booster 4’s later August 11th build site return, SpaceX teams have been hard at work fitting the massive 69m (225 ft) tall rocket booster with thousands of feet (if not miles) of secondary plumbing and power and avionics cables. That process effectively began with removing the Super Heavy’s 29 Raptor engines, which finished just a few days after its return to the high bay.
Now, just 12 days after Super Heavy Booster 4 arrived back at the high bay and 11 days after workers briskly removed its Raptors, SpaceX has begun the process of reinstalling those engines – albeit with several new entrants this time around. When SpaceX first fitted B4 with Raptors, it became clear that five or more of had never been tested, making the removal of some of the Super Heavy’s 29 engines more or less inevitable. Indeed, as expected, several new Raptors (engines that weren’t clearly installed the first time around) have joined around two dozen engines that were installed earlier this month.
Given that Booster 4 has already completed a range of fit checks, the implication is that SpaceX is now installing the 29 Raptor engines that will support the first static fire test campaign of a flightworthy Super Heavy. Of course, that testing (likely involving several different static fires of an increasing number of Raptors) could unearth issues or even damage some of those 29 Raptors, so it isn’t quite accurate to say that Booster 4 is being fitted with the engines that will help it carry Starship to orbit. Depending on the outcome of those tests, though, most could easily find themselves lifting off on Super Heavy B4 later this year.
For now, though, Super Heavy Booster 4’s next milestone will be its second trip from the build site to the launch pad. That could occur at any point in the next week or two and could find Booster 4 installed beside Ship 20 on the second of two suborbital test stands, though the Super Heavy may instead return to the orbital launch site.
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
