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SpaceX schedules second Starship static fire after first test ends prematurely
Update: SpaceX appears to have plans for a second triple-Raptor static fire for Starship SN9 after the rocket’s first test was cut short for unknown reasons.
Identical to previous road closure windows, SpaceX will have an opportunity to test Starship SN9 from 8 am to 5 pm CST (UTC-6) on Friday, January 8th, potentially paving the way for a high-altitude launch attempt early next week if the second static fire goes as planned. Stay tuned for updates!
In what is likely one of the last steps before SpaceX’s next high-altitude Starship launch attempt, the company appeared to successfully put Starship serial number 9 (SN9) through its first triple-Raptor static fire test.
Relatively late into a test window that opened at 8 am CST (UTC-6) but was later pushed to noon, SpaceX’s first Starship SN9 static fire attempt began in earnest around 3:15 pm CST. Signified by venting activity at the propellant farm tasked with preparing and loading liquid oxygen and methane on Starships, slight tweaks in the test flow were observed but the static fire occurred more or less when expected at 4:07 pm.
SN9 ignited all three of its Raptors in quick succession and shut the engines down over the course of 1.5-2 seconds – extremely short relative to all previous nominal Starhopper or Starship-mounted Raptor static fires. Long-time followers immediately noted that small discrepancy, speculating that it could either have been a post-ignition abort or intentionally shortened to avoid damaging the pad’s concrete surface (an incident that’s occurred several times during recent tests).
Not long before the short static fire, SpaceX extended the end of its January 6th test window (in the form of road closure notices) from 5 pm to 8 pm. Oddly, rather than the expected response of detanking Starship and reopening the road after a successful test, SpaceX essentially recycled SN9 and began a separate test around 6 pm. The road was never reopened and a SpaceX team never headed back to the pad between the tests, implying that the company may have run into a minor hardware or software bug earlier in the day.
It’s unclear what the actual goal of the second attempt was and it’s more or less impossible to know for sure with confirmation from CEO Elon Musk. It’s possible – if unlikely – that the first static fire went exactly as planned and the follow-up test was meant to be a simple data-gathering wet dress rehearsal (WDR). Either way, after a surprise downpour briefly engulfed Starship SN9 minutes prior, the second test appeared to abort about 30 minutes into propellant conditioning and loading, precluding both a complete WDR and/or static fire.
According to a test notice received on January 6th by NASASpaceflight contributer and photographer Mary (bocachicagal), SpaceX has another test window available on January 7th in the event that Wednesday’s testing was partially unsuccessful. In a rare case, SpaceX’s hand-distributed warning for residents preceded any additional planned road closures, the last of which lifted on January 6th.
On January 5th, SpaceX received a trio of Temporary Flight Restrictions (TFRs) from the FAA that will allow the company to restrict access to nearby airspace for high-altitude Starship launch attempts on January 8th, 9th, and 10th. Lacking an unequivocally successful static fire, it’s highly unlikely – but not impossible – that Starship will be ready for a launch attempt during any of those three windows. Still, it’s safe to say that SN9 is probably less than a week away from its first flight – expected to be a carbon copy of SN8’s 12.5 km (7.8 mi) launch and landing attempt – if SpaceX can complete a full-duration static fire in the next day or two.
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
