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Boeing's astronaut capsule flies off course, fate uncertain after launch debut
Roughly 30 minutes after lifting off for the first time on a United Launch Alliance (ULA) Atlas V rocket, Boeing’s Starliner crew capsule suffered a major failure when it attempted to raise its orbit with onboard engines.
A few hours after the failure came to light, NASA and Boeing held a press conference to update members of the media on the situation, with the space agency offering some candid – if a bit odd – insight into Starliner’s anomalous launch debut. Before the spacecraft’s software threw a wrench into the gears, the plan was for Starliner to separate from ULA’s Atlas V Centaur upper stage and use its own thrusters to reach orbit and begin the trek up Earth’s gravity well to the International Space Station (ISS).
While it will likely take weeks or even months for Boeing and NASA to determine exactly what went wrong during the mission, preliminary information has already begun to paint a fairly detailed picture.
Around 15 minutes after liftoff, Starliner separated from the rocket as intended but it appears that things began to go awry almost immediately afterward. Most notably, according to NASA administrator Jim Bridenstine’s tweets and later comments, a very early look at the telemetry suggests that Starliner’s internal clock was somehow tricked into believing that the time was either earlier or later than it actually was.
Thinking that it was in the midst of a lengthy thruster firing meant to raise its orbit and send the spacecraft on its way to the space station, Starliner was thus focused on ensuring that it was pointed as accurately as possible. Although the space station is the size of a football field, in the vastness of space, rendezvousing with it is a bit like threading a needle. While firing thrusters to do so, spacecraft thus need to point themselves as accurately as possible.
While coasting before or after one of those orbit-boosting thruster firings, Starliner thought it was actually burning towards the space station and was thus very carefully controlling its orientation with a dozen or so smaller thrusters. In short, those unintentional thruster firings burned through a ton of Starliner’s limited propellant supply – enough to make it impossible (or nearly so) for the spacecraft to rendezvous and dock the ISS, a central purpose of this particular launch.
This ultimately means that Starliner is leaning heavily on the “test” aspect of this Orbital Flight Test (OFT), uncovering failure modes and bugs that Boeing was clearly unable to tease out with ground testing and simulation. While in a totally different ballpark, SpaceX similar Crew Dragon spacecraft suffered its own major failure earlier this year, although that capsule explosion occurred during intentional ground testing, whereas Starliner’s software failed during its high-profile launch debut and has severely curtailed the scope of the spacecraft’s first orbital flight test.
In fact, Bridenstine was unable to rule out the possibility that Boeing will have to attempt a second uncrewed orbital flight test (OFT) before Starliner will be qualified to launch the space agency’s astronauts. Although early signs suggest that Boeing will still be able to attempt to deorbit and recover the spacecraft a day or two from now, the fact that Starliner will not be able to perform critical demonstrations of its ISS rendezvous and docking capabilities will make it far harder for NASA to rationally certify the spacecraft for astronaut launches.
SpaceX’s Crew Dragon, for reference, completed a more or less flawless launch, orbit raise, and rendezvous before docking with the ISS. It’s almost impossible to imagine NASA giving SpaceX permission to proceed immediately into its first astronaut launch if Crew Dragon had failed to reach the proper orbit or dock with the space station.
Regardless, it’s far too early to tell whether Boeing will have to repeat Starliner’s OFT. If Starliner performs absolutely perfectly between now and its planned soft-landing in New Mexico, there might be a chance that NASA will still allow Boeing to effectively cut corners to its astronaut launch debut, but only time will tell.
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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
