News
Tesla China gives sneak peek at Giga Shanghai operations with new video series
Tesla China announced that it would release a series of videos providing a sneak peek into Giga Shanghai’s operations. The first video in the series shares information about Tesla China’s cost management strategy.
Giga Shanghai’s Layout
The first factor in Tesla China’s cost control strategy is Giga Shanghai’s layout. The stamping, welding, painting, and assembly workshops are connected to minimize “the logistics path” between each process, improving efficiency. Giga Shanghai also utilizes the longitudinal space in all its workshops through elevators and machine transportation tracks. The placement of Giga Shanghai’s docks is also a way of running the factory efficiently, which minimizes time and costs.
Elon Musk once stated that Tesla’s gigafactories would become products themselves. Tesla China seems to have taken that to heart with Giga Shanghai.
“It can be said that the innovation of the factory itself builds [an] enforceable foundation for the innovation of the production and manufacturing. Without this foundation, cost control would be like a tree without roots or water without a source,” noted Tesla China.
Take a tour inside Tesla Gigafactory Shanghai and follow us to explore the unique charm of the "Tesla Giga Principle" of cost control.
A series of cool videos will be released later. Don't miss out👀 Let’s #GoGiga 🔥 @elonmusk
🔗https://t.co/7jdNmCipL8— Tesla Asia (@Tesla_Asia) December 16, 2021
Tesla China R&D Center
Tesla’s local R&D Center in Shanghai was completed earlier this year. Tesla China states that the R&D Center is another pillar in its cost management strategy. The R&D Center handles essential parts of Tesla’s manufacturing process from design to testing and quality control.
Tesla China believes the R&D Center provides a complete closed-loop product development process. It helps Giga Shanghai vehicles evolve over time by delivering precise cost management blueprints that improve the affordability of Tesla products, from its all-electric vehicles to its battery storage systems.
Tesla Giga Shanghai Production
Tesla Giga Shanghai’s production process is yet another factor contributing to lowered costs. The process includes independent parts production. An excellent example of independent parts production would be the Tesla Model 3 and Model Y’s single-cast rear bottom plate.
“Take the Model 3 as an example. It needs roughly more than 70 punch-welded parts for the rear bottom plate. Most OEMs usually outsource those parts production, and they still have to set up a welding line,” said one Tesla Chain Casting Process Engineer.
“So, the whole production cycle is quite long. After we realized the one-piece casting, we only need the aluminum ingots from a supplier to manufacture it ourselves, including melting, die-casting, post-treatment, and machining. Within a very short period of time, the raw materials will be molded into a complete rear bottom plate,” he said.
The management of the docks contributes to the efficiency of production as well. The factory handles nearly 2,000 containers a day. Each customer order affects the sequence the factory transports the car parts through the assembly line. Suppliers also follow customer orders by sending parts as each order is made.
Through this level of organization with suppliers and in Giga Shanghai, Tesla China ensures that little to no parts need to be kept in a warehouse. Giga Shanghai aims to have zero inventory.
The supply chain significantly affects production, as can be seen in the way the docks are managed. Localizing Giga Shanghai’s supply chain was crucial in Tesla China’s cost management strategy. The local supply chain helps reduce production costs and raise the standards for parts.
Tesla China’s cost control video provides a tiny glimpse into all the work and forethought that went into Giga Shanghai from layout to production. It also explains why Giga Shanghai has become cost-efficient and Tesla’s primary export hub.
Giga Shanghai has helped increase Tesla’s production and delivery numbers at a monumental level. In November, Tesla China’s Global VP Grace Tao stated that Giga Shanghai aims to produce 500,000 vehicles by the end of 2021.
Watch Tesla China’s Giga Shanghai feature in the video below.
https://youtu.be/esa7iC0MOJ8
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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
