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SpaceX set to launch massive satellite on July 2nd: 3 flights in 9 days

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SpaceX’s Next Launch is Still Nearly on Time in Spite of BulgariaSat-1 Delays

As first reported earlier this morning by James Dean of Florida Today and now officially confirmed by the launch customer Intelsat, SpaceX’s launch of Intelsat 35e has been scheduled for July 2nd at 4:36 p.m. PST.

A several day delay of the launch of BulgariaSat-1 from Monday to Friday of last week was logically assumed to mean that the launch of Intelsat 35e, previously scheduled for July 1st, would be delayed at least several days to allow for the necessary pad checks and repairs that occur after launches. In 2017, this pad flow has generally taken at least a full week, with a static fire occurring once the pad is ready, and a launch several days after that. Two weeks has so far been a relatively consistent minimum between launches from the same pad.

A launch from LC-39A on July 2nd would give SpaceX at most nine days from the launch of BulgariaSat-1 to ready the pad once more. Further, Intelsat 35e has a static fire scheduled as early as Thursday this week, six days after the pad’s previous successful launch. I previously wrote about SpaceX potentially conducting three separate missions within the course of two weeks and declared that such an accomplishment would be a massive accomplishment and proof of concept for some of SpaceX’s more lofty goals. Now it would appear that there is a possibility that SpaceX could launch three separate missions in as few as nine days.

Nine days is of course quite close to being a single week, and successfully pulling off what is now officially scheduled would lend unassailable credence to a previous SpaceX goal of regular, weekly cadence by 2019. In fact, three launches in nine days from two separate pads almost makes regular weekly launches from two separate pads appear imminently in reach for the company, possibly even earlier than 2019.

Intelsat 35e will become the largest communications satellite SpaceX has ever sent to orbit, weighing in at ~6000 kilograms. Designed to last at least 15 years in geostationary orbit, it is expected that SpaceX will attempt to place the satellite into a higher energy geostationary transfer orbit in order to reduce the amount of time it takes the commsat to reach its final planned orbit. This translates to an expendable Falcon 9 Full Thrust that will pushed close to its payload and orbit limits. While it is now somewhat sad to see a Falcon 9 first stage unable to attempt recovery, this will still be a thoroughly exciting launch, especially considering the impressive mass of the satellite.

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Another successful recovery for 1029 on June 23, 2017. Note the dramatic lean and differing angles of the legs on the left, courtesy of a very hard landing. (SpaceX)

SpaceX’s constant iteration of Falcon 9 vehicles meant that Intelsat 35e did not have to wait for Falcon Heavy, as the current default version of the Falcon 9 (v1.2) has begun to overlap the original performance estimates for the first Falcon Heavy concept. Of note, the vehicles that launched last weekend have approximately double the lifting capacity of the original Falcon 9, which last flew in 2013.

The static fire for the launch of Iridium 35e is currently scheduled for this Thursday. Check back at Teslarati for confirmation of that test as we find ourselves once more just a handful of days away from yet another SpaceX launch.

Eric Ralph is Teslarati's senior spaceflight reporter and has been covering the industry in some capacity for almost half a decade, largely spurred in 2016 by a trip to Mexico to watch Elon Musk reveal SpaceX's plans for Mars in person. Aside from spreading interest and excitement about spaceflight far and wide, his primary goal is to cover humanity's ongoing efforts to expand beyond Earth to the Moon, Mars, and elsewhere.

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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.

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Credit: Grok Imagine

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. 

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“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.”

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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.

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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.

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Credit: xAI/X

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.”

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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. 

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Elon Musk’s xAI closes upsized $20B Series E funding round

xAI announced the investment round in a post on its official website. 

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Credit: xAI

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.”

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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. 

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