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SpaceX’s first Starship flight (re)scheduled for next week
SpaceX’s fifth full-scale Starship prototype could become the first to take flight just a week or so from now if a Raptor engine test goes as planned early next week.
Known as Starship serial number 5 (SN5), SpaceX teams are currently in the process of completing the installation of Raptor SN27 and preparing the massive steel rocket for its first cryogenic wet dress rehearsal and static fire tests. Delayed from July 8th and 10th, Starship SN5’s first Raptor static fire is now scheduled no earlier than ~10 am CDT (~15:00 UTC) on Monday, July 13th.
If things go well during those nominally back-to-back tests, public road closure filings show that SpaceX wanted to attempt the first full-scale Starship hop just three days later, although the recent two-day delay adds a bit of uncertainty.
The odds are good that one or both of those test periods will slip or change in the next few days and, in fact, Starship SN5’s static fire test period was delayed two days while this article was in work. SpaceX could run into road bumps that prevent the July 10th 13th wet dress rehearsal (WDR) from smoothly transitioning into a Raptor static fire attempt and any number of additional delays could beset the actual flight test throughout the flow. Along the same lines as Starhopper, currently the only vehicle to have flown under the power of a Raptor engine, Starship’s flight computer could abort the launch at almost any point prior to liftoff, up to and including Raptor ignition.
Like Falcon 9 and Falcon Heavy, Starship (and Starhopper) will ingest and interpret hundreds or thousands of channels of telemetry to determine the health of its engines for a second or two after ignition while thrust is ramping. If the Raptor or Merlin engine(s) look healthy, the rocket commands hold-down clamp release and lifts off (or, in the case of Starhopper, uses its own immense weight to prevent liftoff until Raptor is throttled up).
Thanks to an upgraded launch mount, SpaceX’s full-scale Starship prototypes have access to built-in hold-down clamps, enabling operations that are at least a bit more similar to those used for Falcon 9 and Heavy launches. Starship’s six hold-down clamps are affixed to the same structure that the ship’s six landing legs are installed on.
Perhaps the single biggest point of uncertainty with Starship’s first full-scale test flight is its somewhat mysterious landing legs – almost entirely different from Falcon 9’s well-proven four-leg design. The stubby Starship legs stow inside the ship’s engine section, swinging down and out (and potentially telescoping, albeit much less than Falcon 9) come touchdown. Based on photos of the legs, they may also feature rudimentary shock absorption mechanisms, meaning that Starship should be able to tolerate slightly rougher landings. SpaceX has likely tested Starship leg deployment extensively on the ground but beyond that assumption, they remain an unproven mystery.
Regardless, SpaceX is going to be extremely busy over the next 7-10 days with Starlink-9 scheduled to launch NET July 11th, Starship SN5’s static fire NET July 13th, Falcon 9’s ANASIS II launch scheduled NET July 14th, and a potential SN5 hop test attempt as early as July 16th (speculation).
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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
