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SpaceX Starship prototype charred but intact after catching fire [photos]
SpaceX teams have finally safed the fourth full-scale Starship prototype nearly two days after a Raptor engine test caught it on fire, an anomaly that left the massive rocket charred and damaged – but still intact.
While SN4’s survival is a welcome and unexpected outcome, the fire that broke out near the base of the rocket caused damage that will have to be repaired, while the fault that allowed that fire to occur in the first place will also need to be rectified. Had the same events transpired during the ship’s inaugural flight test, things could have gone even further south after the rocket lifted off, carrying it away from remotely-controlled water jets used to suppress unplanned fires on the pad.
Thankfully, SpaceX’s focus on testing, testing, and testing some more meant that Starship SN4’s minor self-immolation occurred on the ground when the stakes – while high – were much lower than they would have been with an airborne rocket. The problems uncovered will, of course, need to be fixed, inevitably delaying the ship’s first flight test, but odds are that SN4 now has a better shot at success thanks to those hiccups.
Thanks to the fact that Starships are constructed almost entirely out of steel, a little (or a lot of) fire shouldn’t theoretically be much of a problem. However, SpaceX has taken a rather freeform approach to its early Starship SNx prototypes, opting to bolt, weld, or tape on the vast majority of external hardware with little or no protection from the elements, including fires ignited by the ships themselves.
With SN4, it appears that the pressure jump experiences immediately after Raptor ignition (the ship’s third such test) shook some methane-related plumbing loose. Raptor continued to burn for another five or so seconds after that minor failure, shutting down as planned – but not before it ignited the methane the burst pipe was leaking. Additionally, after that new plume of boiling liquid methane caught fire, the fire it sustained proceeded to ignite insulation wrapped around the rocket’s launch. It burned vigorously, likely helping to damage wiring, ultimately causing SpaceX to partially lose control of the rocket and preventing attempts to inspect and fix the damage for two full days.
It’s safe to say that SpaceX is probably going to prioritize avoiding the series of events that caused May 19th’s anomaly from here on out, considering that things could have easily gone much worse. Thankfully, whatever control SpaceX or the rocket itself retained after wire damage allowed it to safely offload its flammable propellant and vent expanding gases to prevent SN4’s tanks from bursting. Installing highly flammable insulation approximately 10 feet away from an active Raptor engine and giant controlled fire and explosion was also inadvisable and probably won’t be repeated.
Thankfully, the damage is clearly minimal and Starship SN4 survived the ordeal otherwise unscathed. With any luck, inspections and repairs will be quick and easy and SpaceX – as NASASpaceflight reporter Michael Baylor notes – will be able to complete an identical static fire test without starting a fire on Starship SN4. SpaceX has requested a new road closure (signifying planned testing) on May 28th with backup windows on May 29th and June 1st.
Thanks to Starship SN4’s unplanned delays, it now looks quite likely that SpaceX’s next full-scale Starship prototype (SN5) will be completed – or nearly so – by the time that its predecessor is cleared for flight. “Too many Starships” is certainly a welcome problem to have.
News
Nvidia CEO Jensen Huang explains difference between Tesla FSD and Alpamayo
“Tesla’s FSD stack is completely world-class,” the Nvidia CEO said.
NVIDIA CEO Jensen Huang has offered high praise for Tesla’s Full Self-Driving (FSD) system during a Q&A at CES 2026, calling it “world-class” and “state-of-the-art” in design, training, and performance.
More importantly, he also shared some insights about the key differences between FSD and Nvidia’s recently announced Alpamayo system.
Jensen Huang’s praise for Tesla FSD
Nvidia made headlines at CES following its announcement of Alpamayo, which uses artificial intelligence to accelerate the development of autonomous driving solutions. Due to its focus on AI, many started speculating that Alpamayo would be a direct rival to FSD. This was somewhat addressed by Elon Musk, who predicted that “they will find that it’s easy to get to 99% and then super hard to solve the long tail of the distribution.”
During his Q&A, Nvidia CEO Jensen Huang was asked about the difference between FSD and Alpamayo. His response was extensive:
“Tesla’s FSD stack is completely world-class. They’ve been working on it for quite some time. It’s world-class not only in the number of miles it’s accumulated, but in the way it’s designed, the way they do training, data collection, curation, synthetic data generation, and all of their simulation technologies.
“Of course, the latest generation is end-to-end Full Self-Driving—meaning it’s one large model trained end to end. And so… Elon’s AD system is, in every way, 100% state-of-the-art. I’m really quite impressed by the technology. I have it, and I drive it in our house, and it works incredibly well,” the Nvidia CEO said.
Nvidia’s platform approach vs Tesla’s integration
Huang also stated that Nvidia’s Alpamayo system was built around a fundamentally different philosophy from Tesla’s. Rather than developing self-driving cars itself, Nvidia supplies the full autonomous technology stack for other companies to use.
“Nvidia doesn’t build self-driving cars. We build the full stack so others can,” Huang said, explaining that Nvidia provides separate systems for training, simulation, and in-vehicle computing, all supported by shared software.
He added that customers can adopt as much or as little of the platform as they need, noting that Nvidia works across the industry, including with Tesla on training systems and companies like Waymo, XPeng, and Nuro on vehicle computing.
“So our system is really quite pervasive because we’re a technology platform provider. That’s the primary difference. There’s no question in our mind that, of the billion cars on the road today, in another 10 years’ time, hundreds of millions of them will have great autonomous capability. This is likely one of the largest, fastest-growing technology industries over the next decade.”
He also emphasized Nvidia’s open approach, saying the company open-sources its models and helps partners train their own systems. “We’re not a self-driving car company. We’re enabling the autonomous industry,” Huang said.
Elon Musk
Elon Musk confirms xAI’s purchase of five 380 MW natural gas turbines
The deal, which was confirmed by Musk on X, highlights xAI’s effort to aggressively scale its operations.
xAI, Elon Musk’s artificial intelligence startup, has purchased five additional 380 MW natural gas turbines from South Korea’s Doosan Enerbility to power its growing supercomputer clusters.
The deal, which was confirmed by Musk on X, highlights xAI’s effort to aggressively scale its operations.
xAI’s turbine deal details
News of xAI’s new turbines was shared on social media platform X, with user @SemiAnalysis_ stating that the turbines were produced by South Korea’s Doosan Enerbility. As noted in an Asian Business Daily report, Doosan Enerbility announced last October that it signed a contract to supply two 380 MW gas turbines for a major U.S. tech company. Doosan later noted in December that it secured an order for three more 380 MW gas turbines.
As per the X user, the gas turbines would power an additional 600,000+ GB200 NVL72 equivalent size cluster. This should make xAI’s facilities among the largest in the world. In a reply, Elon Musk confirmed that xAI did purchase the turbines. “True,” Musk wrote in a post on X.
xAI’s ambitions
Recent reports have indicated that xAI closed an upsized $20 billion Series E funding round, exceeding the initial $15 billion target to fuel rapid infrastructure scaling and AI product development. The funding, as per the AI startup, “will accelerate our world-leading infrastructure buildout, enable the rapid development and deployment of transformative AI products.”
The company also teased the rollout of its upcoming frontier AI model. “Looking ahead, Grok 5 is currently in training, and we are focused on launching innovative new consumer and enterprise products that harness the power of Grok, Colossus, and 𝕏 to transform how we live, work, and play,” xAI wrote in a post on its website.
Elon Musk
Elon Musk’s xAI closes upsized $20B Series E funding round
xAI announced the investment round in a post on its official website.
xAI has closed an upsized $20 billion Series E funding round, exceeding the initial $15 billion target to fuel rapid infrastructure scaling and AI product development.
xAI announced the investment round in a post on its official website.
A $20 billion Series E round
As noted by the artificial intelligence startup in its post, the Series E funding round attracted a diverse group of investors, including Valor Equity Partners, Stepstone Group, Fidelity Management & Research Company, Qatar Investment Authority, MGX, and Baron Capital Group, among others.
Strategic partners NVIDIA and Cisco Investments also continued support for building the world’s largest GPU clusters.
As xAI stated, “This financing will accelerate our world-leading infrastructure buildout, enable the rapid development and deployment of transformative AI products reaching billions of users, and fuel groundbreaking research advancing xAI’s core mission: Understanding the Universe.”
xAI’s core mission
Th Series E funding builds on xAI’s previous rounds, powering Grok advancements and massive compute expansions like the Memphis supercluster. The upsized demand reflects growing recognition of xAI’s potential in frontier AI.
xAI also highlighted several of its breakthroughs in 2025, from the buildout of Colossus I and II, which ended with over 1 million H100 GPU equivalents, and the rollout of the Grok 4 Series, Grok Voice, and Grok Imagine, among others. The company also confirmed that work is already underway to train the flagship large language model’s next iteration, Grok 5.
“Looking ahead, Grok 5 is currently in training, and we are focused on launching innovative new consumer and enterprise products that harness the power of Grok, Colossus, and 𝕏 to transform how we live, work, and play,” xAI wrote.
Nvidia CEO Jensen Huang explains difference between Tesla FSD and Alpamayo
Elon Musk confirms xAI’s purchase of five 380 MW natural gas turbines
