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SpaceX scrubs Starhopper’s final Raptor-powered flight as Elon Musk talks “finicky” igniters
For unknown reasons, SpaceX’s Starhopper prototype suffered a hold just 0.8 seconds prior to its second planned flight test, a hold that was eventually followed by a decision to scrub the August 26th attempt and try again tomorrow, August 27th.
Starhopper is a full-scale, partial-height testbed for SpaceX’s next-generation Starship launch vehicle, serving more as a semi-mobile test stand for steel rockets and Raptor engines than an actual Starship prototype. The unusual vehicle took flight for the first time ever on July 25th, reaching an altitude of roughly 20m (65 ft) under the power of a single Raptor engine, capable of producing up to 200 tons (450,000 lbf) of thrust. That test also suffered a minor scrub on the 24th, followed by a successful flight one day later, a chapter that Starhopper may now mirror on its second attempted flight, a 150m (500 ft) hop.
Notably, SpaceX CEO Elon Musk took to Twitter just seconds after the rocket’s scheduled liftoff suffered a last-second hold to indicate that Raptor’s torch igniters were proving somewhat finicky relative to the chemical alternative used by SpaceX’s proven Merlin engines.
The CEO later confirmed that that comment was directly related to the 26th’s scrub, indicating that Raptor serial number 06 (SN06) needed to have its igniters inspected prior to a second hop test attempt, now scheduled to occur no earlier than 6pm EDT (22:00 UTC) on August 27th. The gist of the difficulties with Raptor’s igniter starts with the reason that SpaceX is attempting to integrate an entirely new form of ignition into the engine, replacing the methods successfully used over tens or even hundreds of thousands of seconds of firing with the company’s Merlin 1 and Merlin Vacuum engines.
Merlin 1D and MVacD both rely on a relatively simple, reliable, cheap, and easy method of chemical ignition, using a duo of pyrophoric materials known as triethylaluminum-triethylborane (TEA-TEB). When mixed, these materials immediately combust, generating an iconic green flash visible during Falcon 9 and Heavy launches, and thus producing the ‘spark’ needed to start Merlin engines.
Generally speaking, TEA-TEB is an excellent method of igniting rockets, even if it is more of a brute-force, inelegant solution than alternatives. It does, however, bring limitations: every single ignition requires a new ‘cartridge’ be expended, fundamentally limiting the number of times Merlin 1D (and Merlin Vacuum) engines can be ignited before and after liftoff.
This doesn’t even consider the fact that TEA-TEB are extremely complex chemical products that would be next to impossible to produce off of Earth, at least for the indefinite future.
To combat these downsides, SpaceX has designed Raptor with an entirely different method of ignition, known as torch ignition. Technically speaking, Raptor’s power, design, and methalox propellant combine to demand more than a relatively common solution, in which spark plugs are used to ignite an engine. Instead, Raptor uses those spark plugs to ignite its ignition sources, what CEO Elon Musk has described as full-up blow torches. Once ignited, those blow torches – likely miniature rocket engines using the same methane and oxygen fuel as Raptor – then ignite the engine’s methane and oxygen preburners before finally igniting those mixed, high-pressure gases in the combustion chamber.
In simple terms, the fact that Raptor is a full-flow staged-combustion (FFSC) engine means that the pressures it must operate under are extreme, verging on unprecedented in large-scale rocketry. Extremely high-pressure gases (on the order of 3,000-10,000+ psi or 200-700+ bar) are just as difficult to reliably ignite, especially if hypergolic solutions (i.e. TEA-TEB) are off the table.
To get an even ignition – critical to avoid burn-through, minor explosions, and even catastrophic engine failures – Raptor’s torch ignition may actually involve a 360-degree ring of spark plug-lit torches around the point of ignition, an undeniably complex solution.
However, as Musk notes, these significant, “finicky” challenges brought on by Raptor’s exotic ignition method are motivated by the potential benefits such a solution might bring. Relative to Merlin 1D’s TEA-TEB ignition, torch ignition – once optimized and matured into a reliable solution – will permit an almost unlimited number of Raptor ignitions before, during, and after flight.
Avoiding TEA-TEB and other complex chemical igniters also means that Starship will technically be able to launch to Mars or the Moon, perform injection and landing burns, maybe even hop around the surface, and still be able to return to Earth – all without resupply. Such a return voyage would still be predicated on the ability to generate the methane and oxygen propellant needed to fuel Starships, but – assuming that challenge can be solved – torch-lit Raptors would be ready for such a mission. In the event that, say, something like August 26th’s scrub happens to a Starship on Mars, the crew would also be able to get out, inspect Starship’s Raptors, and even replace faulty spark plugs if necessary.
Technically, one could bring lots of spare TEA-TEB cartridges and install those in space or after landing, but those cartridges are quite literally firebombs waiting to ignite, whereas spare spark plugs are entirely inert.
For now, we’ll have to wait for SpaceX technicians to get their eyes and hands-on Starhopper’s lone Raptor engine to verify that its ignition hardware is in good health. If all goes well, Starhopper will attempt its final flight test as early as August 27th.
Update (August 27th): Starhopper is reportedly set for a second attempted 150m (500 ft) flight test today, scheduled to occur no earlier than 5pm EDT (21:00 UTC) on August 27th. Stay tuned for SpaceX’s official Livestream!
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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
