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SpaceX go for Starlink launch, landing as ULA rocket delays persist
SpaceX is on track for Falcon 9’s latest Starlink launch and landing later today as delays continue to hamper a United Launch Alliance (ULA) rocket meant to lift off more than a month ago.
In fact, an almost identical scenario played out a month ago as SpaceX and ULA coincidentally aligned to attempt two launches less than a day apart. The pad hardware supporting ULA’s Delta IV Heavy NROL-44 mission suffered several delays on August 26th and 27th, followed by a dramatic post-ignition launch abort on August 29th. Throughout, SpaceX effectively had to sit on its hands and wait for permission to launch Falcon 9’s SAOCOM 1B mission. Historically, it’s been safe to assume that a ULA mission – particularly one like NROL-44 – would unilaterally take precedence over a SpaceX launch, forcing the company to wait indefinitely until the range was clear.
Instead, in a major twist, SpaceX received permission to launch – and ultimately did launch – SAOCOM 1B on August 30th with ULA’s Delta IV Heavy and its multibillion-dollar NROL-44 payload still on the launch pad. In essence, one or several stakeholders in the military mission have become confident enough in the reliability of SpaceX’s rockets to no longer perceive a nearby Falcon launch as a major risk. Now, just a month after the development, SpaceX appears to be on track to repeat the feat.

Three days after SAOCOM 1B lifted off from Cape Canaveral Air Force Station (CCAFS) Launch Complex 40 (LC-40), a separate Falcon 9 rocket launched SpaceX’s 12th Starlink mission (Starlink-11) from Kennedy Space Center (KSC) Launch Complex 39A (Pad 39A). Starlink-12 is also scheduled to launch no earlier than (NET) 10:22 am EDT (14:22 UTC), September 28th from Pad 39A, a bit less than six miles (9.5 km) north of the ULA rocket and NROL-44 satellite at LC-37.
SAOCOM 1B was such a surprise because the unique southerly trajectory saw Falcon 9 fly almost directly above LC-37, meaning that an in-flight failure could have very likely showered ULA’s pad, rocket, and payload with debris. LC-40, however, is just a little over two miles (3.5 km) north of LC-37. In other words, a Starlink launch heading northeast from Pad 39A is clearly of little concern to ULA or the NROL-44 launch customer, particularly after SAOCOM 1B was allowed to launch under far riskier conditions.

Instead, the real test of the SAOCOM 1B precedent will come when SpaceX prepares for the mission scheduled after Starlink-12 – the company’s third launch of an upgraded GPS III satellite (SV04) for the US military. As of now, ULA’s next NROL-44 launch attempt is tentatively scheduled around midnight (~04:00 UTC) on September 29th. Shortly thereafter, Falcon 9 is scheduled to launch GPS III SV04 (from LC-40) as early as 9:55 pm EDT (01:55 UTC) that same day.
Given the sheer number of difficulties ULA has had with LC-37 pad systems on this launch attempt, it’s reasonable to assume that NROL-44 will slip beyond September 29th. If that happens, stakeholders will once again have to decide if SpaceX can launch two miles to the north or has to wait for ULA. Either way, tune in tomorrow morning to catch SpaceX’s Starlink-12 launch webcast. Weather at Kennedy Space Center is currently 60% go for launch.
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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.