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SpaceX’s Falcon Heavy fairing tries to enter hyperspace, lands in net in new videos
SpaceX and CEO Elon Musk have released videos offering an extended look at the unexpectedly dramatic conditions Falcon payload fairings are subjected to during atmospheric reentry, as well as the first successful landing in GO Ms. Tree’s net.
Captured via an onboard GoPro camera during Falcon Heavy’s June 25th launch of the USAF Space Test Program-2 (STP-2) mission, the minute-long cut shows off a light show more indicative of a spacecraft entering hyperspace than the slightly more mundane reality. Shortly after SpaceX posted the reentry video, CEO Elon Musk followed up with a video showing a fairing’s gentle landing in Ms. Tree’s net. More likely than not, the fairing with the camera attached and the fairing that became the first to successfully land in Mr. Steven’s (now GO Ms. Tree’s) net are the same half. Regardless, the videos help document a major step forward towards SpaceX’s ultimate goal of fairing reuse.
“In a pleasant, last-minute surprise, SpaceX fairing recovery vessel Mr. Steven has departed Port Canaveral for its first Falcon fairing catch attempt in more than half a year. The speedy ship has already traveled more than 1250 km (800 mi) in ~48 hours and should soon be in position to attempt recovery of Falcon Heavy Flight 3’s payload fairing halves.
Over the last week or two, Mr. Steven has been officially renamed to GO Ms. Tree, a strong indicator that Guice Offshore (GO) – a company SpaceX is heavily involved with – has acquired the vessel from financially troubled owner/operator Sea-Tran Marine. With this likely acquisition, nearly all of SpaceX’s non-drone ship vessels are now leased from – and partially operated by – GO. The name change is undeniably bittersweet for those that have been following Mr. Steven’s fairing recovery journey from the beginning. However, it’s also more than a little fitting given that the vessel switched coasts and suffered an accident that forced SpaceX to replace the entirety of its arm-boom-net assembly. Much of Mr. Steven – now GO Ms. Tree – has been replaced in the last few months and with any luck, the vessel is better equipped than ever before to snag its first Falcon fairing(s) out of the air.”
— Teslarati.com, June 24th
As they say, the rest is history. Some 60-75 minutes after Falcon Heavy lifted off from Pad 39A on June 25th, Ms. Tree successfully caught a parasailing fairing for the first time ever, just barely snagging one of the two halves at the very edge of the ship’s net. Two days later, Ms. Tree arrived back at Port Canaveral. Another 24 hours after that, the intact, dry fairing half was safely lifted onto land and transported to a local SpaceX facility dedicated to analyzing (and eventually refurbishing) recovered Falcon fairings.
Landing on Ms. Tree pic.twitter.com/4lhPWRpaS9— Elon Musk (@elonmusk) July 4, 2019
With any luck, the successful catch will prove that the years of work have been worth it, demonstrating that fairing halves caught – rather than fished out of the ocean – are structurally sound and clean enough to be quickly and affordably reused. While Falcon fairings have been estimated to take up less than 10% of the material cost of Falcon 9 production (~$6M, $3M/half), the manufacturing apparatus needed to build them takes up a huge amount of space. Additionally, the process of oven-curing huge, monolithic carbon fiber fairings introduces fundamental constraints that physically limit how quickly they can be built.
Fairing reuse would be an invaluable benefit for SpaceX’s internal Starlink launches, of which dozens and – eventually – hundreds will be needed to build an operational constellation of satellites. Thanks to the wonders of Falcon 9 Block 5 booster reuse, the internal cost of a flight-proven booster is essentially just the cost of refurbishment and then the propellant and work-hours needed to launch it. What remains is the cost of the expendable Falcon upper stage (unlikely to be recovered or reused) and payload fairing, now reasonably consistent at landing intact on the ocean surface but yet to demonstrate practical reusability.
As proposed, SpaceX’s completed Starlink constellation represents almost 12,000 satellites. Assuming no progress is made with packing density, no larger payload fairing is developed, and Starship doesn’t reach orbit until the mid-2020s (admittedly unlikely), Starlink will require almost exactly 200 Falcon 9 launches, each carrying 60 satellites. According to Musk, despite the fact that the first 60 satellites launched were effectively advanced prototypes, the cost of launch is already more than the cost of satellite production.
Speaking at a conference in 2017, Musk noted that payload fairings cost about $6M to produce, roughly 10% of Falcon 9’s $62M list price. In 2013, Musk stated that the first stage represented less than 75% of the overall cost of Falcon 9 production, meaning that the rocket’s upper stage probably represents another 15-20% (call it a 70:20:10 split), or ~$9-12M. Conservatively assuming that the operating costs of Falcon 9 refurbishment, launch, and recovery are roughly $5M per mission, the internal cost to SpaceX for a launch with a recoverable flight-proven booster and an expended fairing and upper stage could be just $20-25M and may be even lower.
For reference, assuming 200 Falcon 9 launches, SpaceX could save nearly $600M by consistently recovering and reusing just one fairing half on average per launch, up to as much as $1.2B if both halves can be consistently recovered and reused. June 25th’s successful fairing catch is the biggest step yet in that direction and is hopefully a sign of many good things to come for SpaceX’s latest attempt at building truly reusable rockets.
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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
