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SpaceX CEO Elon Musk details orbital refueling plans for Starship Moon lander
After a much-anticipated GAO denial of Blue Origin and Dynetics protests over NASA’s decision to solely award SpaceX a contract to turn Starship into a crewed Moon lander, an in-depth (but heavily redacted) document explaining that decision was released on August 10th.
Aside from ruthlessly tearing both companies’ protests limb from limb, the US Government Accountability Office’s decision also offered a surprising amount of insight into SpaceX’s HLS Starship proposal. One of those details in particular seemed to strike an irrational nerve in the online spaceflight community. Specifically, in its decision, GAO happened to reveal that SpaceX had proposed a mission profile that would require as many as 16 launches to fully fuel a Starship Lander and stage the spacecraft in an unusual lunar orbit.
After around 24 hours of chaos, confusion, and misplaced panic, SpaceX CEO Elon Musk finally weighed in on the GAO document’s moderately surprising indication that each Starship Moon landing would require sixteen SpaceX launches.
Confirming many expectations, SpaceX’s solution to sending an entire single-stage Starship to the Moon, landing it on the lunar surface, and returning it to a lunar orbit (and maybe even Earth) goes as follows.
First, SpaceX will launch a custom variant of Starship that was redacted in the GAO decision document but confirmed by NASA to be a propellant storage (or depot) ship last year. Second, after the depot Starship is in a stable orbit, SpaceX’s NASA HLS proposal reportedly states that the company would begin a series of 14 tanker launches spread over almost six months – each of which would dock with the depot and gradually fill its tanks.
Third, once the depot ship is topped off, the actual Starship Moon lander would launch, dock with the depot, and be fully fueled. Finally, the fueled lander would fire up its Raptor engines and head to the Moon, where it would enter a near-rectilinear halo orbit (NRHO) – a weird high-altitude, elliptical orbit only necessary because NASA’s Orion spacecraft and SLS rocket are too underpowered to reach a more normal, functional orbit around the Moon.
After reaching NRHO, Starship would dock with Orion (or vice versa), receive its Artemis astronauts, land on the Moon for several days, and launch back to NRHO to return those astronauts to Orion. After its main mission is complete, it remains to be seen if Starship will have enough propellant left over to return to some kind of Earth orbit, where it could potentially be refueled and reused on future missions to the lunar surface.
In response to GAO revealing that SpaceX proposed as many as 16 launches – including 14 refuelings – spaced ~12 days apart for every Starship Moon lander mission, Musk says that a need for “16 flights is extremely unlikely.” Instead, assuming each Starship tanker is able to deliver a full 150 tons of payload (propellant) into orbit after a few years of design maturation, Musk believes that it’s unlikely to take more than eight tanker launches to refuel the depot ship – or a total of ten launches including the depot and lander.
But, as Musk notes, so long as Starship gets anywhere close to its design objectives, it would be a non-issue even if each Starship Moon lander mission somehow required 16 launches. A step further, assuming that SpaceX proposed 16 launches per mission out of an abundance of conservatism, it’s fair to assume that a 12-day gap between tanker launches is also an extremely conservative worst-case scenario. Per Musk and SpaceX, Starship’s design goals call for multiple reuses of ships and boosters per day. Even if SpaceX falls a full magnitude short of those ambitious goals, Starship tankers should feasibly be able to launch every few days or maybe every week.
But thanks to SpaceX’s relatively conservative proposal, the company now knows that NASA is more than happy with Starship even if it falls something like 50% short of its payload performance goals and two magnitudes short of its reusability goals.
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
