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Report: SpaceX to launch at least five back-to-back Crew Dragon missions for NASA
Update: Wasting no time at all, NASA has confirmed the Ars Technica report one day later, announcing that rookie astronauts Nicole Mann and Josh Cassada have been reassigned from Boeing Starliner missions to SpaceX’s Crew-5 Crew Dragon launch – currently no earlier than August 2022.
Ars Technica’s Eric Berger reports that NASA has begun the process of moving a number of astronauts assigned to Boeing’s ailing Starliner spacecraft to a SpaceX Crew Dragon mission scheduled no earlier than August 2022.
Per sources close to Berger, NASA has chosen to reassign two rookie astronauts to Crew Dragon as hopes of a crewed Starliner launch – and thus an opportunity for them to gain hands-on spaceflight experience – in the next 6-12 months continue to wither. Barring surprises, the implied change of plans behind those actions means that SpaceX now appears to be scheduled to fly five operational NASA Crew Dragon missions back to back before Boeing’s Starliner flies a single astronaut – let alone its first operational mission with four crew aboard.
In December 2019, nine months after Crew Dragon’s own uncrewed March 2019 debut, Starliner lifted off for the first time on a ULA Atlas V rocket. However, whereas Crew Dragon performed a practically flawless orbital launch, space station rendezvous, docking, departure, reentry, and splashdown on its first try, Starliner’s Orbital Flight Test (OFT) went horribly wrong as soon as it separated from Atlas V.
Due to shoddy prelaunch testing that failed to detect several gaping holes in Starliner’s software, the spacecraft effectively lost control as soon as it was under its own power. Aside from making ground communication and control far harder, Starliner burned through most of its propellant and pushed most of its maneuvering thrusters past their design limits in the first hour or two after launch. Due to the catastrophic software failure and lack of propellant margins, NASA unsurprisingly called off a planned space station rendezvous and docking attempt and Boeing ultimately ordered Starliner to reenter a few days after launch.
Mere hours before reentry, Boeing apparently detected and fixed another major software error at the last second, potentially preventing Starliner’s propulsion and service module from smashing into the capsule’s fragile heat shield and dooming the spacecraft to burn up during reentry. Ultimately, it’s likely that the only reason Boeing didn’t suffer a total loss of vehicle (LOV) during Starliner’s OFT debut spacecraft was dumb luck. Had the initial clock error been worse, Starliner could have failed to reach orbit entirely or burned through all of its propellant, resulting in an uncontrolled reentry. Had there been no clock issue, it’s hard to imagine that Boeing’s software team would have attempted the panicked, impromptu bug hunt that detected and fixed the service module recontact issue.
Now, 22 months after Starliner’s catastrophic OFT, Boeing has been forced to stand down from a second self-funded orbital flight test (OFT-2) due to the last-second discovery of more than a dozen malfunctioning valves on the second spacecraft’s service module. Aside from raising the question of how Boeing and NASA yet again failed to detect a glaring Starliner issue until the day of launch, Starliner’s valve issues appear likely to cause another multi-month delay as Boeing is forced to investigate the problem, find the root cause, and implement a fix on all impacted service modules.
NASA reassigning some of the astronauts scheduled to helm Starliner on its Crewed Flight Test (CFT) and first operational mission to Crew Dragon’s August 2022 Crew-5 launch seemingly implies that the space agency is not confident that Boeing will have completed Starliner OFT-2, passed extensive post-flight reviews, and readied another Starliner for CFT by Q3 2022. Given that NASA took some 14 months to OK Crew Dragon’s Demo-2 crewed flight test after Demo-1’s March 2019 success and a catastrophic April 2019 failure during a ground test of the recovered capsule, it’s not unreasonable to assume that NASA will take about a year after OFT-2 to approve Starliner’s first crewed flight test.
If significant issues arise during OFT-2, which is now unlikely to occur before early 2022, a year-long gap is even more likely. Ultimately, that means that there is now a significant chance that SpaceX’s Crew Dragon spacecraft will complete not just five – but six – back-to-back operational NASA astronaut launches before Starliner is ready for its first operational ferry mission. SpaceX, in other words, is now expected to singlehandedly hold the line and ensure biannual NASA access to and from the International Space Station (ISS) for more than two years despite charging NASA $2 billion less than Boeing (~$5B vs ~$3B) to develop Crew Dragon.
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
