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SpaceX just finished its third Starship rocket in two months and a fourth is on the way
SpaceX just rolled a completed Starship prototype to the launch pad for the third time in two months and began stacking the next rocket just hours after its assembly facilities were vacated.
SpaceX began building the latest Starship prototype – known as serial number 4 (SN4) – around March 23rd. Exactly 31 days later, SpaceX lifted the vast steel rocket onto a Roll Lift transporter and carried it roughly a mile down the road to the company’s Boca Chica, Texas test and launch facilities. In just a few hours, technicians lifted the rocket off its transporter and onto a fixed launch mount made out of thick steel beams, expediency made possible partly by the addition of new mounting points and hold-down clamps.
Sitting atop the late Starship SN3 prototype’s salvaged skirt, landing leg, and service section, the fate of Starship SN4 remains to be seen and the path it has taken to the pad is paved with the remains of several former prototypes. For the most part, that should be a positive aspect. Given how apparent it is that SpaceX is very quickly learning from past mistakes, SN4 has the best chance yet of successfully passing its proof tests and graduating into Raptor static fire and (perhaps) flight testing. However, if things don’t go as planned, SpaceX is perhaps just a week or two away from completing the next prototype – Starship SN5.
A few hours after SpaceX lifted Starship SN4 onto its steel launch mount, CEO Elon Musk revealed an aerial photo of the rocket and its pad facilities taken with a drone. Recently painted gray and refurbished to undo damage done by Starship SN3’s April 3rd, that mount is currently configured with a strong metal frame and three powerful hydraulic rams. A nearly identical jig was damaged during SN3’s last test when a minor tsunamic of liquid nitrogen – used to safely simulate ultra-cold and explosive liquid oxygen and methane propellant – washed over the mount after the rocket burst.
Much like an ice cube can violently crack and pop when it rapidly changes temperature, untreated steel (almost always cheaper than the alternative) can also be catastrophically damaged by rapid temperature changes (thermal shock). This appears to be exactly what happened to the first hydraulic ram mount, which had visible cracks in photos taken after Starship SN3’s April 3rd demise.
SpaceX appears to have had no issue at all acquiring a replacement in a matter of weeks and it arrived and was installed several days ago. The purpose of the hardware is relatively simple: simulate the stresses one or three Raptor engines will create when ignited and ensure Starship’s ‘thrust puck’ and engine section can survive those stresses while filled with cryogenic liquid methane.
Each ram attaches to the thrust puck with the same hardware an actual Raptor uses, including the rods each engine needs for thrust vector control (TVC; i.e. active steering). In the event that Starship SN4 passes its cryogenic proof test(s) and engine stress simulation(s) with flying colors, SpaceX has already built, acceptance-tested, and shipped three Raptor engines to Boca Chica, where they are waiting inside an assembly tent for their call to action.
Once a Starship prototype passes acceptance testing and three Raptor engines can be installed, it will be a first for SpaceX’s next-generation rocket engine. For example, if SN4 makes it through testing and is ready to proceed into static fire operations, it will be the first time Raptor has operated in a multi-engine setup – always a significant milestone for any launch vehicle, including SpaceX’s own Falcon 9 and Merlin engines.
In case SN4 does make it to the other side, SpaceX is already prepared with both road closures and NOTAMs (Notices To Airmen) for static fire and hop tests spread out over the next week or so.
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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
