News
SpaceX is about to reuse (part of) a Starship rocket
SpaceX has apparently decided to reuse a large section of a Starship prototype that was accidentally destroyed during testing earlier this month, a first for the next-generation rocket.
While not quite the same kind of ‘reuse’ SpaceX has largely pioneered with its vertically-landing Falcon rocket boosters, the company’s decision to reuse an unflown section of a former Starship prototype is yet another sign of its prioritization of efficiency and speed. The Starship SN3 hardware SpaceX has chosen to repurpose on Starship SN4 is relatively straightforward relative to almost all other sections of the newest prototype, but it should still save the company a not-insignificant amount of time and money.
For SpaceX, a combination of extraordinary speed and efficiency at its nascent South Texas Starship factory is allowing the company to accomplish feats that would otherwise be impossible. At least as important, fast and cheap Starship manufacturing has meant that SpaceX is far more willing (perhaps even a little too willing) to take risks with any given prototype, partly explaining why the company is about to complete its fourth full-scale Starship in as many months.

A few days after Starship SN3 was destroyed by some combination of operator error and a badly-designed test, CEO Elon Musk confirmed suspicions that part of the rocket – appearing effectively unscathed – could be reused on the next prototype.
Speaking on April 5th, Musk actually indicated that “much” of Starship SN3’s thrust section could be reused, referring to roughly the bottom third of the rocket’s tank section. Located at the aft (rear) end of Starship, the engine section is where 3-6 Raptor engines attach to the rocket and must safely transfer their thrust through the rest of the vehicle while also feeding those engines propellant and redistributing high-pressure gases to the ship’s main tanks. As a result, engine sections are often some of the most complex and labor-intensive parts of rocket production.


It appears that Musk wound up being partially correct with his initial judgement. On April 15th, eight days after Starship SN3’s remaining aft section was cut in half, the rearmost half – known as the skirt – was spotted stacked beneath a brand new engine section built for SN4. While confirming that a significant part of SN3 will be reused on SN4, it also indicates that only a less critical SN3 remnant was fit to join SpaceX’s next prototype.
Recently confirmed by Musk after a Teslarati article on the topic, Starship SN3’s skirt section – while not the more complex engine section and thrust structure – has been fitted with six landing legs in anticipation of the first full-scale Starship flight tests.


Aside from landing legs, the reused SN3 skirt also includes substantial structural reinforcements, ground umbilical connections for propellant, power, and telemetry, and built-in hold-down clamps. While fairly small in the scope of an entire Starship, SN4’s adoption of SN3’s skirt should help speed the new rocket towards completion and the start of its first test campaign. Barring surprises, SpaceX will almost certainly move Starship SN4 to its nearby testing facilities within the next several days to a week.
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.