News
SpaceX’s first two Super Heavy boosters making good progress towards test debuts
SpaceX is making good progress on Starship’s first two Super Heavy boosters, both of which could potentially be ready for their first major test campaigns before the end of the year.
On November 19th, some ten weeks after the process began, SpaceX craned Super Heavy B5’s methane (LCH4) tank on top of its oxygen (LOx) tank, marking the end of major structural assembly for the 69m (~225′) tall booster. A team of welders has since been working around the clock to weld the two tanks together and complete a transfer tube that routes methane propellant down through B5’s oxygen tank.
Two days prior, CEO Elon Musk shared a photo of SpaceX’s other Super Heavy booster (B4) which has been slowly progressing towards test readiness for more than three months. It’s unclear why SpaceX has been so sluggish to prepare Super Heavy B4 for testing but with B5 finally approaching the finish line, the company will soon find itself in a position where it will need to decide which booster to proceed with towards the program’s near-term end goal: the first orbital Starship test flight.
Once Booster 5’s two halves are welded together, only a few things will set it and Booster 4 apart. In recent weeks, SpaceX’s slow progress on Super Heavy B4 relented a bit as technicians began closing out the booster’s raceway (a conduit for plumbing, wiring, and avionics) with basic covers. More importantly, SpaceX also began reinstalling Raptor engines and installing heat shielding around those engines for the first time. In the photo Musk published on November 17th, that heat shield is easily visible and there are signs that it will ultimately enclose the entire outer ring of 20 Raptor Boost engines above their nozzles.
Once complete, that shield will theoretically protect each engine’s nest of sensitive plumbing and wiring during static fires; ascent, boostback, and landing burns; and – most importantly – reentry. Unlike Falcon boosters, which always perform a ~30-second, three-engine ‘reentry burn’ to slow down and cushion the blow of reentry heating, SpaceX plans to recover steel Super Heavy boosters without reentry burns. In theory, that should making booster recovery more efficient, allowing another dozen or so tons of propellant to go towards sending Starship to orbit instead of landing.
As of November 17th, SpaceX has reinstalled all 29 Raptor engines on Booster 4, partially finished the outer ring of Raptor heat shields, and set the stage for more heat shielding around its 9 center engines and the gap between those inner and outer Raptors. Shielding the Raptor Center engines in a way that still seals off Super Heavy’s aft will be even more challenging given that all nine need to be able to freely gimbal to vector their thrust, while the outer ring of 20 Raptor Boost (RB) engines are fixed in place. At pace of work established over the last few months, it will likely take SpaceX several more weeks to finish that heat shield and install seven ‘aerocovers’ over racks of sensitive equipment installed around Booster 4’s base.
Super Heavy Booster 5, on the other hand, has taken a slightly different path through assembly. Unlike Booster 4, which first rolled out as little more than a giant steel tank with Raptors half-installed, SpaceX appears to have installed most of Booster 5’s external plumbing, wiring, equipment racks, and maybe even the start of its Raptor heat shield during assembly instead of after. Perhaps as a result, SpaceX has taken more than ten weeks to stack Booster 5 versus 2.5 weeks for Booster 4. But given that Booster 4 still doesn’t appear to be complete some 18 weeks after its assembly began, there’s a chance that Booster 5 will ultimately take 4-6 weeks less to reach initial test readiness.
If SpaceX does complete Super Heavy B5 well ahead of B4’s schedule, it will soon find itself with two test-ready Starship boosters but only one orbital-class stand with which to test them, potentially forcing the company to make some interesting decisions.
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
