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SpaceX scraps Starship SN8 wreckage, clears landing zone for next launch
In spite of tentative plans for preservation, SpaceX has fully scrapped the wreckage of the first high-altitude Starship prototype, clearing the landing zone it impacted for its successor’s imminent launch debut.
Known as serial number 8 or SN8, the Starship prototype was the first of any kind to fly beyond 150 meters (~500 ft), reaching an altitude of 12.5 km (~7.8 mi) on December 9th during its breathtaking launch debut. In an unexpected twist, SpaceX kept Starship SN8’s thrust to weight ratio as low as possible, stretching what could have been a two or three-minute test into an almost seven-minute ordeal with three consecutive Raptor engine cutoffs during the ascent.
At apogee, SN8 used cold gas thrusters to flip into a belly-down orientation and free-fell ~95% of the way back to Earth before igniting two of its three Raptor engines, performing a wild powered flip back into a vertical landing position and nearly securing a soft landing. Unfortunately, around 10-20 seconds before that planned landing, what Musk later described as low methane header tank pressure starved the Starship’s engines of fuel and more or less cut all appreciable thrust, causing SN8 to reach its landing zone traveling about 40 m/s (~90 mph) too fast. The rocket impacted the concrete pad, crumpled, and exploded.
By all accounts, success was one of the less likely outcomes SpaceX expected from SN8’s high-altitude debut, with Musk himself estimating the odds of total success to be just 33%. Additionally, Starship SN8 effectively made it all the way to a low-speed landing regime that Starships SN5 and SN6 all but flawlessly demonstrated with back-to-back 150m hops and landings in August and September 2020.
In other words, despite the explosive end, SN8’s high-altitude launch debut was a spectacular success for SpaceX’s Starship program – possibly even preferable to a perfect landing given that it uncovered an unexpected issue with fuel tank pressurization. Beyond the landing failure, the Starship checked every single box on SpaceX’s test flight list, successfully debuting multiple Raptors, demonstrating multiple in-flight engine shutdowns and engine relights; proving that an unprecedented ‘skydiver-style’ landing maneuver is possible and viable; and successfully testing Starship’s ability to control itself in that bellyflop orientation with thrusters and four massive flaps.
Speaking in a recent interview with Ars Technica, in the words of pragmatic SpaceX COO and President Gwynne Shotwell, SN8’s launch debut “de-risked [the Starship] program pretty massively.” According to Musk, SpaceX engineers were quickly able to determine why Starship SN8’s methane header tank was unable to maintain the fuel flow (pressure) needed for Raptor’s landing burn(s) and quickly implemented a solution.
Instead of pressurizing autogenously with methane gas, Starship SN9 will use helium to pressurize its fuel header tank, serving as a temporary fix while SpaceX determines what changes need to be made to get rid of that helium crutch. Landing pad now cleared of Starship remains and SN8’s impact crater more or less repaired, the only thing standing between Starship SN9 and its own 12.5 km launch debut is a triple-Raptor static fire test. Originally expected as early as January 4th, SpaceX never made it more than a few minutes into the attempt, while a backup window on January 5th was canceled later that evening. The test could now occur no earlier than (NET) Wednesday, January 6th.
Thankfully, although SpaceX was unable to save the entirety of Starship SN8’s wrecked nose section, the company did manage to extract a largely intact nose flap. The rest of the remains were scrapped on site and trucked away but it’s possible that certain significant components of SN8 – particularly the recovered flap – will eventually find themselves on display at one or more SpaceX facilities.
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
