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Tesla’s Gigafactory formula rose from a humble “tent” at the Fremont Factory
Back in 2018, Tesla was in a very different place. The company was struggling to release the Model 3, and it was behind on Elon Musk’s aggressive self-imposed vehicle production targets. The Fremont Factory’s assembly lines were not producing enough Model 3s, and it seemed like the company was poised to fail. Critics and shorts circled Tesla like sharks smelling blood in the water. But something unexpected happened, and things were never the same after.
Throwing convention out the window, Tesla built another Model 3 line inside a massive sprung structure at the Fremont Factory grounds, which CEO Elon Musk fondly called a “tent” online. The structure, dubbed as GA4, was mocked to the highest degree, used as a joke by critics, and dismissed outright by skeptics. However, what was almost unknown at the time was that Tesla might have actually stumbled into something special with its sprung structure-based line. By building a simple, straight, Model 3 line inside a “tent,” Tesla seems to have effectively created a solid Gigafactory formula.
No standard automotive solution could be built in time, so we created a new solution. It is working & has slightly higher quality than the more traditional general assembly line. Perhaps most surprising is that the total cost of production in the Sprung tent is lower.
— Elon Musk (@elonmusk) June 27, 2018
A Practical Concept
The sprung structure-based Model 3 line was the brainchild of Automotive President Jerome Guillen, widely known as Elon Musk’s “problem solver” back in the Model S’ early days. The “tent”-based line followed a relatively simple system, with vehicles being assembled progressively the further they moved into the tent. Even GA4’s loading bays were placed on the sides of the structure, allowing Tesla to take deliveries into the line efficiently. Musk was enthusiastic about the sprung structure on Twitter, noting not long after the “tent” was built that the vehicles produced in the site had “slightly higher quality” than cars made elsewhere.
These humble but creative beginnings appear to have become the heart of Tesla’s Gigafactory formula, one used in Giga Shanghai and Giga Berlin, and seemingly improved further with Gigafactory Texas. This could be seen in the design and processes that Tesla has adopted so far in its Shanghai and Berlin plants, both of which invoke the image of a scaled-up, refined, and optimized version of Fremont’s “tent.”
A Gigafactory Formula
Tesla critics typically overlook the fact that the Fremont Factory is a legacy car plant at its core. It’s an expansive facility, and it is impressive in its own right, but it’s not a site developed specifically to produce all-electric cars. Thus, for the Model S, Model X, and the Model 3’s early days, Tesla was essentially developing a system that makes EVs at scale using a facility designed initially to manufacture cars equipped with the internal combustion engine.
Of course, Tesla has made numerous adjustments to make the Fremont Factory into one of the most advanced electric vehicle plants in the market. However, it is difficult not to be impressed with Tesla’s quick production ramp and flexibility in Gigafactory Shanghai, arguably the first EV factory that the company built using its GA4 formula, with its simple production lines to its numerous loading bays at its side. This concept seems to have been carried over to Gigafactory Berlin, which is expected to ramp its operations at a rate that rivals even that of Giga Shanghai.
A Matter of Scale
Ultimately, it appears that GA4 was Tesla’s “eureka” moment of sorts, at least for its electric vehicle factories. By scaling up and refining the sprung structure-based concept, Tesla was able to create monster factories like Giga Shanghai, and later this year, Gigafactory Berlin as well. However, this is not all as Tesla seems to be adopting an updated design for Gigafactory Texas, with its three main buildings built parallel with each other. Little is known about the reasons behind Giga Texas’ design, but there’s little doubt that the expansive facility will be very impressive when completed nonetheless.
Prior to the Model 3’s “production hell,” Elon Musk spoke about Tesla’s “Alien Dreadnought” factories, which are supposed to be so automated and advanced that they would resemble alien facilities featured in sci-fi fiction. Tesla seems to have shelved this idea following the Model 3’s challenges in its initial production ramp. With an established Gigafactory formula of sorts in its repertoire, however, and coupled with innovations such as the Model Y’s megacasts, Elon Musk’s dreadnoughts may not be too far into the future at all.
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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.”
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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
