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SpaceX rapidly shipping upgraded Raptor engines to Starbase
SpaceX appears to have opened the floodgates and begun shipping upgraded ‘Raptor V2’ engines to Starbase en masse in preparation for crucial Starship and Super Heavy testing.
The first functional Raptor engine delivery in around half a year and the first Raptor V2 delivery ever appeared to arrive at Starbase on March 30th. About a month and a half prior, SpaceX brought an early Raptor V2 prototype damaged during testing to serve as a backdrop for CEO Elon Musk’s February 10th Starship presentation, marking the first time the public was allowed to see or photograph the engine up close.
Less than three months later, Raptor V2 engines that passed proof testing without damaging or destroying themselves have begun to rapidly pile up inside one of Starbase’s three main production tents.
Though Raptor V2 has plenty in common with its Raptor V1 and V1.5 predecessors and, for the most part, looks very similar, Musk has repeatedly stated that the engine represents a major evolution from past Raptors. Most importantly, Raptor V2 was designed to significantly cut production cost and time. To achieve that, almost every major component was either fully redesigned, tweaked, or refined in some way to make Raptor simpler and more compact.
One example is the decision to slash the number of flanges (mechanical joints) in the engine’s plumbing by replacing them with welds. Making plumbing more monolithic could remove dozens of parts, seals, and potential leak points and significantly speed up manufacturing at the cost of making it harder – if not impossible – for SpaceX to inspect and replace certain pipes or pipe sections in a modular manner.
That process was repeated throughout each Raptor system, resulting in an engine that looks more streamlined than earlier variants. As a result of its more refined design and improvements to other critical components, Musk says that even though Raptor V2 now costs about half as much to build as V1.5, it’s also “much more…reliable.”
Despite significantly improving Raptor’s reliability, simplicity, and cost, SpaceX also managed to boost its maximum thrust by almost 25%. Raptor V2 engines now “routinely” operate at record-breaking main combustion chamber pressures of 300+ bar (~4400 psi) and are able to produce up to 230 tons (~510,000 lbf) of thrust at sea level. The older Raptor V1.5 engines that flew on Starships SN8-SN11 and SN15 and were installed on Super Heavy Booster 4 and Ship 20 were designed to produce around 185 tons (~410,000 lbf) at 250 bar (~3600 psi).
Following the premature retirement of Super Heavy Booster 4 (B4), which was meant to help send Starship S20 to space on the rocket’s first orbital launch attempt, that orbital launch debut is now guaranteed to use a different booster and ship powered by Raptor V2 engines. Ship 24 is a strong candidate for the mission’s Starship, while it remains to be seen if SpaceX will fully repair and attempt to proceed with Booster 7 or if Booster 8 – which is almost complete – will take point.
Either way, the pair will need at least 39 qualified Raptor V2 engines to begin integrated testing, pass several major static fire milestones, and prepare for flight. Since SpaceX appeared to kick off Raptor V2 deliveries to Starbase on March 30th, a photo shared by Musk on April 26th revealed that the company has managed to deliver at least 18 of the upgraded engines in the last four weeks. At least one more engine was also delivered on April 28th.
That means that SpaceX already has enough engines to begin static fire tests with a full cluster of 13 central Raptors on Super Heavy B7 or B8. By the time Ship 24 is fully assembled, Booster 7 is repaired, or Booster 8 is completed, there’s a good chance that SpaceX will have all the engines it needs to fully outfit a Starship and Super Heavy pair – not quite by the end of April, as Musk predicted, but not far off.
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
