News
SpaceX begins stress-testing upgraded Super Heavy booster
In a what is likely a prelude to engine installation, SpaceX has begun stress-testing an upgraded Super Heavy booster prototype.
Known as Super Heavy Booster 7 or B7, the prototype is the first of its kind designed to support up to 33 new Raptor V2 engines – each potentially capable of producing up to 230 tons (~510,000 lbf) of thrust at liftoff. Even with just 20 such engines installed, Super Heavy – measuring around 69 meters (~225 ft) tall and nine meters (~30 ft) wide – will be the largest and most powerful rocket stage ever tested. That potentially unprecedented power is why SpaceX has custom-built a complex structural test stand to explore Super Heavy’s true performance envelope in a slightly less risky manner.
In the second half of 2021, that structural test stand briefly tested an unusual half-Starship, half-Super Heavy test tank with a nine-engine thrust section (‘puck’) and later compressed a different test tank until its reinforced steel skin buckled. In the interim, SpaceX removed its nine-ram setup and modified the stand to support 13 rams, guaranteeing that its new purpose was to test Super Heavy’s new 13-engine thrust section. Prior to Booster 7, all Super Heavy prototypes have had a similar nine-engine puck and an outer ring of 20 engines that would attach directly to the rim of each booster’s cylindrical body.
Increasing the central engine count from 9 to 13 was already certain to up the amount of stress future Super Heavy thrust pucks would need to survive by almost 45%. But combined with Raptor V2’s thrust increases, Super Heavy Booster 7’s thrust puck could actually be subjected to at least 80% more thrust at liftoff. Altogether, Super Heavy B7’s 33 engines should be able to produce ~7600 tons (~16.8M lbf) of thrust compared to Super Heavy B4’s ~5400 tons (~11.9M lbf). As a result, though it’s odd that SpaceX never did significantly test Booster 4, it’s no surprise that the company chose to give Booster 7 priority as soon it was ready.
After a few false starts and at least one ‘pneumatic proof test’ that likely saw Booster 7 pressurized with benign nitrogen gas, SpaceX began stress-testing the upgraded Super Heavy in earnest on April 14th. First, the booster was filled about a third of the way with roughly 1000 tons (~2.2M lb) of liquid nitrogen (LN2) or a combination of liquid oxygen (LOx) and LN2. Once the rocket was fully chilled, there were clear signs of some kind of added stress as large sheets of ice that had formed on the side of B7’s skin broke apart and fell off.
Only ice close to Super Heavy’s base was visibly disturbed, increasing the odds that the behavior was a sign of some or all of the structural test stand’s hydraulic rams simulating Raptor engines. It’s also possible that the stress was caused by pressurizing Super Heavy’s tanks to the point that they began to appreciably deform, though that type of testing is far harder to differentiate. Without official comments, it’s unfortunately impossible to ever know what exactly SpaceX is testing or how successful those tests are when the structural test stand is involved.
Nonetheless, it’s likely that Booster 7 isn’t done with the stand just yet. SpaceX could benefit from just about any data gathered about the performance of Super Heavy’s new thrust puck during simulated Raptor startup, throttling, and shutdown both at liftoff and during boostback and landing burns. SpaceX might also want to simulate engine-out scenarios that would result in asymmetric thrust.
Assuming Booster 7 survives this particular series of tests and SpaceX is happy with its performance on the structural test stand, the upgraded Super Heavy could be ready for Raptor installation and integrated wet dress rehearsal and static fire testing in the near future. SpaceX began delivering upgraded Raptors V2 engines to Starbase in late March.
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.