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SpaceX’s next Starship gets frosty to prepare for first launch
One week after the rocket was rolled from the factory to the launch pad, SpaceX appears to have successfully put Starship serial number 9 (SN9) through two routine pre-launch tests.
On December 22nd, significantly less than two weeks after Starship SN9 suffered a significant handling or production accident that caused it to tip several degrees and impact the walls of its production facility, SpaceX wrapped up speedy repairs and transported the rocket about 1.5 miles down the road.
In some combination of a minor miracle and Starship’s exceptionally sturdy design, the rocket – standing ~50 meters (~165 ft) tall and weighing around 75 to 100 metric tons (175,000-220,000 lb) – tipped sideways onto two of its four pre-installed flaps. Despite being subjected to off-nominal forces, the far stronger structural mechanisms connecting those flaps to Starship’s main airframe were seemingly unharmed and SpaceX was able to remove and replace the crumpled control surfaces mere days after the incident.
On December 28th, that work began in earnest with what is generally known as an ambient temperature pressure test, filling Starship SN9’s propellant tanks with benign air-temperature nitrogen gas. Used to check for leaks, verify basic vehicle valve and plumbing performance, and ensure a basic level of structural integrity, SN9 appeared to pass its ambient proof test without issue – albeit late in the window.
Testing wrapped up on Monday shortly after the ambient proof and was followed by the main event – a cryogenic proof test – a bit less than a day later on Tuesday. The exterior of Starship SN9 began to develop a coating of frost after SpaceX started loading its oxygen and methane tanks with liquid nitrogen around 2:30 pm CST (UTC-6). While used similarly to verify structural integrity like an ambient pressure test, a ‘cryo proof’ adds the challenge of thermal stresses to ensure that Starship can safely load, hold, and offload supercool liquids.
In SN9’s case, it’s unclear if SpaceX fully or only partially loaded the rocket’s main propellant tanks with liquid nitrogen, while a lack of frost at the tip of its nose implies that the Starship’s smaller liquid oxygen ‘header’ tank wasn’t filled as part of the test. Altogether, Starship should be capable of holding roughly 1200 metric tons of liquid nitrogen if fully loaded.
The lack of SN9’s LOx header tank participation in Tuesday cryo proof testing is intriguing on its own, as it implies that SpaceX will either perform a second cryo proof later this week or is confident enough in LOx header tank and transfer tube performance to forgo any testing. In the latter case, SpaceX would likely just use the build-up to Starship SN9’s first Raptor static fire test as a wet dress rehearsal (WDR) and a cryo proof for the smaller tank system.
According to NASASpaceflight’s managing editor, if Monday and Tuesday’s ambient and cryo proof tests were as uneventful and successful as they seemed, SpaceX may move directly on to triple-Raptor static fire preparations. In a first, Starship SN9 was transported to the launch pad last week with two of three central Raptor engines already installed and had that missing third engine installed within a few days of arrival. SN9 is also the first Starship to attempt its first proof tests with any Raptor – let alone three – installed.
If SpaceX does move directly from cryo proof testing to a three-engine static fire, that will mark another first for the Starship program and signal growing confidence and a desire for speedier preflight tests – both of which will help accelerate flight testing. As of now, SpaceX has yet to cancel a road closure scheduled on Wednesday, December 30th but it’s far more likely that a trio of 8 am to 5 pm CST closures requested on January 4th, 5th, and 6th will host Starship SN9’s first static fire attempt(s). According to NASASpaceflight.com, Starship SN9 is expected to attempt a 12.5 km (~7.8 mi) launch similar or identical to SN8’s as early as a few days after that static fire. Stay tuned for updates!
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
