News
SpaceX drone ship fleet aces two Falcon 9 booster recoveries in 48 hours
SpaceX’s two-vessel drone ship fleet has successfully returned two boosters from sea to port in the space of just ~40 hours, an impressive feat that simultaneously shed light on a new kind of bottleneck for Falcon launches.
Completed on January 20th and 24th and originally planned as few as 25 hours apart, SpaceX’s back-to-back Starlink-16 and Transporter-1 launches made it clear that drone ship availability could quickly become a constraint as the company eyes increasingly ambitious launch cadence targets. CEO Elon Musk has stated that SpaceX is targeting up to 48 launches in 2021, translating to an average of one launch every 7.5 days.
As it turns out, measured from port departure to port arrival, that target is practically the same as the average amount of time it takes one of SpaceX’s two drone ship landing platforms to complete a booster recovery. Both existing drone ships must be slowly towed to and from the booster landing area, generally involving a minimum round trip of 800 miles (~1300 km) and some five days in transit.

In other words, even given a perfectly optimized schedule in which SpaceX launches missions requiring at-sea recovery every ~180 hours throughout 2021, each mission would have just a handful of days worth of margin before one launch delay would inherently delay another launch. Fundamentally, with a fleet of two drone ships requiring an average of five days of transit time per recovery, SpaceX could theoretically support as many as ~70 booster recoveries annually assuming zero downtime, no launch delays, and mere hours spent at the landing zone before turning around and heading back to port.
To be clear, recovery ship availability is an excellent problem to have, as it implies that SpaceX is fast approaching a rate of launch (and routine rocket landings) unprecedented in the history of commercial spaceflight. Thankfully, SpaceX also has an exceptional track-record of solving hard problems and there remains a great deal of ‘slack’ to be optimized out of its fleet of recovery ships.

That is all to say that removing the fundamental bottlenecks posed by SpaceX’s existing fleet will absolutely require at least one or two new drone ships on top of at least two major oil rig conversion projects in work for Starship. Whether in the form of one or more new converted barges or some kind of faster, self-propelled vessel, it’s safe to say that new ships are virtually guaranteed and likely close at hand unless SpaceX has decided to accept a semi-arbitrary ceiling on annual East Coast launches.
Just one month into 2021, SpaceX’s two drone ships are already being stretched to their operational limits to the point of launch delays. Delayed from January 17th to January 20th, Starlink-16 held up drone ship Just Read The Instruction for several days, resulting in the vessel returning to port on the 24th, just ~60 hours prior to Starlink-17’s original January 27th launch target. With drone ship Of Course I Still Love You (OCISLY) already indisposed at sea to support SpaceX’s January 24th Transporter-1 launch, SpaceX had to move Starlink-17 to January 30th.
After a few days in port for booster processing and maintenance, drone ship JRTI ultimately departed Port Canaveral for Starlink-17 on the evening of the 27th, most likely delaying the launch to Sunday, January 31st. For now, though, Falcon 9 booster B1049 is scheduled to launch for eighth time no earlier than (NET) 7:24 am EST (12:24 UTC), January 30th. Simultaneously, drone ship Of Course I Still Love You will likely need to depart Port Canaveral later this weekend to support Starlink-18, scheduled to launch as soon as 1:19 am EST, February 4th.
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.