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SpaceX Super Heavy booster aces static fire test on the first try
CEO Elon Musk says that SpaceX has successfully fired up Super Heavy – the largest rocket booster in the world – on the first try, potentially opening the door for a significantly more ambitious ‘static fire.’
Known as Booster 3 (B3), SpaceX completed Starship’s first functional Super Heavy prototype around July 1st and rapidly rolled the rocket out and installed it on a customized mount previously used for testing and launching Starship prototypes. After a bit less than two more weeks spent finishing up Booster 3’s avionics and plumbing and installing one Raptor engine, Super Heavy sailed through its first cryogenic proof test attempt on July 12th.
Rather than flammable liquid methane and oxygen propellant, Super Heavy was loaded with liquid nitrogen – providing roughly the same extremely cold temperature and mass without risking a massive explosion. In the week after that success, technicians rapidly installed two more Raptor engines and completed final closeout work on the building-sized rocket. On July 19th, Super Heavy B3 came alive for the second time.
After a delay to this week, SpaceX closed the road, cleared the launch pad, and began fueling Super Heavy for the first time ever around 6:20 pm CDT (UTC-5) – six hours into Monday’s ten-hour window. Almost exactly mirroring a routine Starship wet dress rehearsal or static fire, the pad and rocket followed a well-documented choreography of tank farm activity, vents, and frost formation, culminating in Booster 3 successfully igniting three Raptor engines around 7:05 pm.
Unlike virtually all Starship prototypes ever tested, including the first fully-assembled ships’ first multi-Raptor static fires, Super Heavy Booster 3 – the first functional prototype of its kind – completed its first static fire ever on the first try. In the history of Starship testing, initial prototypes have never smoothly sailed through cryogenic proof or static fire tests on the first attempt. Almost without fail, minor to major issues have arisen either before or during initial test attempts as SpaceX worked through the basics of operating Starship tests.
Instead, despite the fact that B3 is quite literally the largest rocket booster prototype ever built in the history of spaceflight and the first of its kind, Super Heavy appeared to run into no obvious issues at all after it was properly prepared for its first two major tests. Put simply, Super Heavy’s smooth testing makes it abundantly clear that SpaceX’s Starship launch vehicle design, production, and operations are rapidly maturing as the company speeds towards its first orbital launch attempt.
Meanwhile, Elon Musk says that SpaceX “might try a 9 engine firing on Booster 3” depending on how Booster 4 production progresses – presumably over the next week or two. By all appearances, SpaceX began stacking Super Heavy B4 – the booster tasked with supporting Starship’s first orbital launch attempt around July 16th. Based on B3 assembly, Booster 4 could be complete by mid to late August.
With nine Raptors installed, Super Heavy B3 could produce up to 1800 tons (~4 million lbf) of thrust during a brief static fire – just ~20% less than Falcon Heavy. Stay tuned for updates on Booster 3 and Booster 4!
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
