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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Elon Musk
Tesla’s Elon Musk: 10 billion miles needed for safe Unsupervised FSD
As per the CEO, roughly 10 billion miles of training data are required due to reality’s “super long tail of complexity.”
Tesla CEO Elon Musk has provided an updated estimate for the training data needed to achieve truly safe unsupervised Full Self-Driving (FSD).
As per the CEO, roughly 10 billion miles of training data are required due to reality’s “super long tail of complexity.”
10 billion miles of training data
Musk comment came as a reply to Apple and Rivian alum Paul Beisel, who posted an analysis on X about the gap between tech demonstrations and real-world products. In his post, Beisel highlighted Tesla’s data-driven lead in autonomy, and he also argued that it would not be easy for rivals to become a legitimate competitor to FSD quickly.
“The notion that someone can ‘catch up’ to this problem primarily through simulation and limited on-road exposure strikes me as deeply naive. This is not a demo problem. It is a scale, data, and iteration problem— and Tesla is already far, far down that road while others are just getting started,” Beisel wrote.
Musk responded to Beisel’s post, stating that “Roughly 10 billion miles of training data is needed to achieve safe unsupervised self-driving. Reality has a super long tail of complexity.” This is quite interesting considering that in his Master Plan Part Deux, Elon Musk estimated that worldwide regulatory approval for autonomous driving would require around 6 billion miles.
FSD’s total training miles
As 2025 came to a close, Tesla community members observed that FSD was already nearing 7 billion miles driven, with over 2.5 billion miles being from inner city roads. The 7-billion-mile mark was passed just a few days later. This suggests that Tesla is likely the company today with the most training data for its autonomous driving program.
The difficulties of achieving autonomy were referenced by Elon Musk recently, when he commented on Nvidia’s Alpamayo program. As per Musk, “they will find that it’s easy to get to 99% and then super hard to solve the long tail of the distribution.” These sentiments were echoed by Tesla VP for AI software Ashok Elluswamy, who also noted on X that “the long tail is sooo long, that most people can’t grasp it.”
News
Tesla earns top honors at MotorTrend’s SDV Innovator Awards
MotorTrend’s SDV Awards were presented during CES 2026 in Las Vegas.
Tesla emerged as one of the most recognized automakers at MotorTrend’s 2026 Software-Defined Vehicle (SDV) Innovator Awards.
As could be seen in a press release from the publication, two key Tesla employees were honored for their work on AI, autonomy, and vehicle software. MotorTrend’s SDV Awards were presented during CES 2026 in Las Vegas.
Tesla leaders and engineers recognized
The fourth annual SDV Innovator Awards celebrate pioneers and experts who are pushing the automotive industry deeper into software-driven development. Among the most notable honorees for this year was Ashok Elluswamy, Tesla’s Vice President of AI Software, who received a Pioneer Award for his role in advancing artificial intelligence and autonomy across the company’s vehicle lineup.
Tesla also secured recognition in the Expert category, with Lawson Fulton, a staff Autopilot machine learning engineer, honored for his contributions to Tesla’s driver-assistance and autonomous systems.
Tesla’s software-first strategy
While automakers like General Motors, Ford, and Rivian also received recognition, Tesla’s multiple awards stood out given the company’s outsized role in popularizing software-defined vehicles over the past decade. From frequent OTA updates to its data-driven approach to autonomy, Tesla has consistently treated vehicles as evolving software platforms rather than static products.
This has made Tesla’s vehicles very unique in their respective sectors, as they are arguably the only cars that objectively get better over time. This is especially true for vehicles that are loaded with the company’s Full Self-Driving system, which are getting progressively more intelligent and autonomous over time. The majority of Tesla’s updates to its vehicles are free as well, which is very much appreciated by customers worldwide.
Elon Musk
Judge clears path for Elon Musk’s OpenAI lawsuit to go before a jury
The decision maintains Musk’s claims that OpenAI’s shift toward a for-profit structure violated early assurances made to him as a co-founder.
A U.S. judge has ruled that Elon Musk’s lawsuit accusing OpenAI of abandoning its founding nonprofit mission can proceed to a jury trial.
The decision maintains Musk’s claims that OpenAI’s shift toward a for-profit structure violated early assurances made to him as a co-founder. These claims are directly opposed by OpenAI.
Judge says disputed facts warrant a trial
At a hearing in Oakland, U.S. District Judge Yvonne Gonzalez Rogers stated that there was “plenty of evidence” suggesting that OpenAI leaders had promised that the organization’s original nonprofit structure would be maintained. She ruled that those disputed facts should be evaluated by a jury at a trial in March rather than decided by the court at this stage, as noted in a Reuters report.
Musk helped co-found OpenAI in 2015 but left the organization in 2018. In his lawsuit, he argued that he contributed roughly $38 million, or about 60% of OpenAI’s early funding, based on assurances that the company would remain a nonprofit dedicated to the public benefit. He is seeking unspecified monetary damages tied to what he describes as “ill-gotten gains.”
OpenAI, however, has repeatedly rejected Musk’s allegations. The company has stated that Musk’s claims were baseless and part of a pattern of harassment.
Rivalries and Microsoft ties
The case unfolds against the backdrop of intensifying competition in generative artificial intelligence. Musk now runs xAI, whose Grok chatbot competes directly with OpenAI’s flagship ChatGPT. OpenAI has argued that Musk is a frustrated commercial rival who is simply attempting to slow down a market leader.
The lawsuit also names Microsoft as a defendant, citing its multibillion-dollar partnerships with OpenAI. Microsoft has urged the court to dismiss the claims against it, arguing there is no evidence it aided or abetted any alleged misconduct. Lawyers for OpenAI have also pushed for the case to be thrown out, claiming that Musk failed to show sufficient factual basis for claims such as fraud and breach of contract.
Judge Gonzalez Rogers, however, declined to end the case at this stage, noting that a jury would also need to consider whether Musk filed the lawsuit within the applicable statute of limitations. Still, the dispute between Elon Musk and OpenAI is now headed for a high-profile jury trial in the coming months.
Tesla’s Elon Musk: 10 billion miles needed for safe Unsupervised FSD
Tesla earns top honors at MotorTrend’s SDV Innovator Awards
