News
SpaceX’s first flight-proven Starship rolled back to factory for likely retirement
While SpaceX has spent the better part of three weeks inspecting the first flight-proven Starship to survive a high-altitude launch and landing, the company appears to have decided to retire the rocket instead of flying it again.
On May 25th, four days after Starship serial number 15 (SN15) was reinstalled on one of SpaceX’s two suborbital launch mounts, a crane was attached to its nose and a transporter staged beside it. One day later, the historic Starship prototype was lifted off of Mount B, installed on that transporter, and rolled away from the launch pad and back towards SpaceX’s Boca Chica, Texas Starship factory.
The day after Starship SN15 was reinstalled on a launch mount, giving SpaceX unrestricted access to its aft, all three of the rocket’s flight-proven Raptor engines – the first of their kind to survive the flight profile intact – were removed. Given the significant value of tearing down and inspecting the first flight-proven high-altitude Raptors, that removal was likely guaranteed regardless of the future of SN15, though it certainly left the Starship at a crossroads.
Having already had its six used landing legs removed, Starship SN15 was left more or less declawed on the launch mount as fans watched with bated breath to see if new legs or engines would be installed. For better or worse, while CEO Elon Musk did indicate that SpaceX “might try to refly SN15 soon” less than two days after its historic landing, it quickly became clear that the company had decided against reuse.
To a degree, especially if SN15’s flight-proven Raptor engines were rendered unusable – as they appear to have been – by exposure to water immediately after touchdown, “reusing” the Starship would be more symbolic than anything. With a thorough inspection, it would be easy enough to determine that the Starship’s structures and mechanical/hydraulic systems would be up for a second launch, but the slow ~10 km (6.2 mi) flight profile ships SN8 through SN11 and SN15 completed was already only relevant for testing Starship’s exotic, unproven method of landing.
In that sense, another fully successful ~10-km launch and landing would only benefit Starship development insofar as it would increase confidence in the landing profile by proving that the first success wasn’t a fluke – however incredibly unlikely that might be. Of note, SpaceX also has not plans to recover the first space-proven Starship, instead (nominally) performing a soft-landing in the Pacific Ocean if the prototype makes it through its inaugural spaceflight without issue.
If that “Orbital Test Flight” is a perfect success, SpaceX will likely have enough confidence – and regulators enough data – to proceed to the first attempt to recover an orbital Starship on land. In the meantime, with orbital launch site buildup now moving at a breakneck pace and tens of millions of dollars of custom pad hardware, giant cranes, and months of work sitting a few hundred feet away from the landing pad, attempting to push the envelope with SN15 likely just isn’t worth the risk.
SN15 is also a historic piece of hardware after its successful landing and there are signs – namely the location SpaceX has moved the rocket to – that the Starship will be put on permanent display beside the factory that built it. There’s a limited possibility that Starship SN16 – all but finished – could be sent to the launch site instead of heading straight to the scrapyard, but any testing would necessarily delay orbital pad construction and any flight activity would likely have to expend SN16 in the ocean rather than risk a land landing.
Ultimately, it’s looking more and more likely that SpaceX would rather go all-in on Starship’s inaugural orbital launch attempt, even if that means little to no ground or flight test availability for a few months.
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
