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SpaceX Starship prototype in limbo after engine test lights rocket on fire
The fate of SpaceX’s fourth full-scale Starship prototype appears to be in limbo after a third (seemingly successful) engine ignition test unintentionally caught the rocket on fire.
Now more than 12 hours after Starship SN4 fired up its new Raptor engine, the ~30m (~100 ft) tall, 9m (~30 ft) wide prototype is apparently trapped with one or both of its propellant tanks still partially filled with liquid (or gaseous) methane and/or oxygen. An initial road closure scheduled from noon to 6pm local quickly came and went and SpaceX and Cameron County Texas have since modified the paperwork, extending the closure a full 24 hours. In other words, SpaceX has reason to believe that Starship SN4 may continue to be unsafe (i.e. pressurized) as many as ~30 hours after it technically completed its third static fire test – extremely unusual, to say the least.
There’s only one obvious conclusion to draw. Whether it was something invisible to the public eye or damage related to the off-nominal fire that burned for some 15 minutes after Raptor shut down, SpaceX appears – to some extent – to have lost control of Starship SN4.
At the moment, it’s unclear what is wrong and what SpaceX is attempting to do to resolve the problem. Based on photos of Starship SN4 taken before the fire, there is good news and bad news from what can be publicly ascertained. Controlled from the ground by unprotected wires strung up and down the rocket and connected at its base, the uncontrolled fire that burned in at least two locations around Starship’s aft may have severed some or all of those critical connections.
That would render Starship – potentially perfectly healthy and operational – almost entirely uncontrollable, while also potentially removing SpaceX’s access to telemetry. In other words, the company may currently have no idea how pressurized all or part of Starship SN4 is and may also have little to no control of some or all of the rocket. For that to be true, Starship SN4 would, however, have to have less than fully redundant control hardware. To perform hops, for example, the ship would need both wired and radio links capable of sending telemetry and receiving commands to remain both on the ground and after liftoff.
It’s possible that Starship SN4 has the necessary hardware installed but that it wasn’t activated for the static fire test (think “Starship will never leave the ground, why would we need to enable wireless controls?”). It’s also possible that the blown pipe and methane leak that appeared to cause the secondary fire damaged crucial propellant management hardware (valves, pumps, etc.) or was just a symptom of an even worse overpressure event that damaged or destroyed multiple such systems.
Given that safety is almost certainly the priority, chances are that some combination of fairly mild hardware failure and telemetry/control loss has left SpaceX with just enough uncertainty that it can’t risk sending technicians to the launch site to inspect the damage and reestablish control. As a result, the only option left is to quite literally sit and wait until it’s once again safe to approach the rocket. Thankfully, at this point, the risk of the mystery problem actually destroying Starship SN4 is very low. If, as it appears, only its methane tank is affected, leaving some unknown quantity of latent liquid methane trapped inside, it’s possible that waiting will actually solve the problem and safe the rocket.
The fact that Starship hasn’t exploded yet strongly implies either that the amount of propellant trapped is minuscule or that the vast majority of SN4’s propellant management systems (including vents) remain functional. Assuming that’s the case, any remaining cryogenic propellant will eventually boil into gas, increasing the pressure inside Starship’s tanks, while those tanks will continue to vent to prevent an explosion or rupture. Eventually, Starship SN4 will be empty once again and SpaceX will be able to approach the rocket to regain control and begin inspections and repairs.
Regardless, after such an unintentionally eventful static fire test, it’s extremely unlikely that SN4 will be ready for its inaugural flight test within the next few days. Stay tuned for updates as SpaceX works to regain control over the fourth full-scale Starship prototype.
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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
