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NASA to retry Artemis I Moon rocket launch on Saturday
NASA says it has alleviated issues that arose during its first Space Launch System (SLS) Moon rocket launch attempt and will try again as early as Saturday, September 3rd.
Measuring around 98 meters (~322 feet) tall and capable of launching up to 95 tons (~210,000 lb) to low Earth orbit, the SLS rocket’s first launch – Artemis I – will attempt to send NASA Orion spacecraft on its way to lunar orbit. If all goes to plan, a partial prototype of the deep space crew transport vehicle will enter orbit spend several weeks around the Moon, where it will attempt to prove that Orion is safe and ready to launch NASA astronauts.
Approximately six years behind schedule and tens of billions of dollars over budget, the combined Orion spacecraft and SLS rocket were originally expected to debut in 2016 when Congress legally required NASA to develop the combined system in 2011. It would be difficult for the stakes to be much higher.
Now, after an unsuccessful August 29th launch attempt that turned into a wet dress rehearsal test as a result of poor planning, NASA is ready to try again.
SLS is scheduled to lift off from NASA’s Kennedy Space Center (KSC) LC-39B pad no earlier than (NET) 2:17 pm EDT (18:17 UTC) on Saturday, September 3rd. Like the first, the window lasts for two hours, providing some flexibility for NASA to troubleshoot any other minor problems that might crop up during the second launch attempt.
During the first SLS launch attempt, several problems arose, including a possible crack in Core Stage foam insulation, a misbehaving vent valve, a hydrogen fuel leak, and weather concerns that delayed the start of propellant loading by more than an hour. The most important problem, causing NASA to abort its first attempt at T-40 minutes to liftoff, involved Core Stage engine chill systems.
At the time, available data suggested that one of the Core Stage’s four modified and flight-proven Space Shuttle Main Engines (known as RS-25) was unable to chill down to the temperatures required for safe ignition. In a September 1st press conference, after more analysis, NASA now says that the rocket was, in fact, correctly trickling liquid hydrogen fuel through all four engines and that all engines were likely ready to go. The agency and its contractors say they are confident that the true cause of the unfavorable readings was a faulty temperature sensor.
In an earlier press conference, senior officials noted that the Boeing-built SLS Core Stage is designed in a way that makes those faulty temperature sensors virtually inaccessible without major work – and certainly not while the rocket is still at the launch pad. A rollback to NASA’s Vehicle Assembly Building (VAB) could easily delay the next SLS launch attempt by 4-6 weeks, if not longer.
Perhaps as a result of the looming consequences of another rollback, instead of sending the rocket back to fix the newly discovered sensor issue, NASA officials now say they never actually needed the broken sensor and can get by without it working properly. That doesn’t entirely explain why NASA fully aborted an SLS launch attempt as a direct result of not liking the data produced by said sensor a few days prior. Nonetheless, the officials say that by analyzing several other unspecified telemetry readings within the RS-25s and SLS plumbing, they can effectively infer that the engines have been chilled to the right temperature.
In theory, if no other issues arise in the remaining 40 minutes leading up to launch, that should allow NASA to confidently launch SLS without having to replace components deep within the rocket.
NASA will begin live coverage of its next SLS launch attempt on NASA TV at 5:45 am EDT (09:45 UTC), followed by a separate hosted broadcast (the agency’s first attempt at a 4K launch webcast) beginning at 12:15 pm EDT (16:15 UTC).
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
