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SpaceX Starship prototype returns to factory after simulated Raptor testing
A SpaceX Starship prototype that could become the first to launch into space has returned to the company’s Starbase rocket factory after completing a series of thorough proof tests.
Starship S24’s test campaign got off to a rough start when the roughly nine-meter (30 ft) wide, 50-meter (~165 ft) tall rocket blew a high-pressure pipe during its very first test – a generally benign ‘pneumatic proof.’ While it appears that most of the ship passed the test, the burst pipe damaged a section of the heat shield and took several days of continuous work to repair and replace. With that hiccup behind it, however, Ship 24 appears to have performed excellently during the next two phases.
On June 1st, the ship fully passed pneumatic proof testing on the second try. On June 2nd, it completed its first cryogenic proof test, referring to the process of filling and pressurizing Starship’s tanks with liquid nitrogen – ultra-cold like its methane and oxygen propellant but without the risk of fire or explosion. Once the basics were out of the way, Ship 24 was cleared for installation on one of two of SpaceX’s suborbital Starship test and launch pads. Over the course of about two months, Pad A was significantly modified both to support Ship 24’s upgraded design and to put it to the test by using giant hydraulic rams to simulate the thrust of Raptor engines.
Ship 24 was installed on the modified mount on June 4th, just 12 hours after completing its first cryoproof. On June 6th and 7th, SpaceX then put the prototype through another pair of cryogenic proof tests, both of which appeared to be completed without issue on the first try. The first test even saw Ship 24 use its nose vents, suggesting that SpaceX may have filled and pressurized both its main tanks and a smaller pair of landing propellant or ‘header’ tanks.
At some point during either or both of the Pad A cryoproofs, it’s believed that the mount’s hydraulic rams were used to test Ship 24’s upgraded aft end by simulating the thrust of six Raptor engines. Like Ship 20, Ship 24 will eventually be outfitted with three smaller sea level-optimized Raptors and three larger vacuum-optimized Raptors. However, Ship 24 will be the first Starship to use new Raptor 2 engines, which are capable of generating almost 25% more thrust. At full throttle, Ship 24 could theoretically produce almost 1400 tons (~3.1M lbf) of thrust at sea level, just shy of twice the thrust of an entire Falcon 9 booster. Starship will be the most powerful orbital spacecraft in history.
First, though, the rocket needs engines. After completing all three cryoproof tests without apparent issue, SpaceX removed Ship 24 from Pad A and transported it back to the Starbase factory on June 9th. While it’s not actually clear if those tests were fully successful, the general assumption is that SpaceX returned the prototype to the factory to fill gaps in its heat shield; complete its aerocovers and raceway; and, most importantly, install six Raptor 2 engines.
If that is the case, Ship 24’s second trip to the launch site could be for wet dress rehearsal and static fire testing – a campaign that could ultimately qualify the ship for Starship’s first orbital launch attempt.
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
