News
The strategy behind the state selection of the Tesla Gigafactory
By now, everyone who has any interest at all in Tesla Motors has heard about their plans for a Gigafactory. Since the plan was introduced in February, the discussion groups and forums have been filled with thoughts on the implications of the huge battery making installation. Four potential sites were named: New Mexico, Nevada, Arizona and Texas.
Speculation about how this would change things became rampant. Nicolas Zart asked how it would affect Tesla’s long-standing relationship with Panasonic, who provides the batteries being used in the Model S and that will likely be used in the upcoming Model X. Yet a more persistent question in the peanut gallery has been why Tesla would choose the states it mentioned as candidates for the factory.
To be straightforward, there was a lot of strategic thinking that went behind the choice of the four states mentioned, and there’s a good reason that a couple of those states, deemed as “Tesla-unfriendly,” are on the list.
Logistics
The states chosen are all within a specific logistical area. They’re warm weather states, have little seismic activity, are within easily-accessed and well-established transportation corridors (trains, highways, etc.), have low-cost land available, and have a surplus of most energy types.
This means that transport of materials and finished products to and from each of these locations is relatively easy and requires minimal work to customize. All of them are in sunny locations (a primary requirement for a solar farm as large as Tesla proposes) and they all have access to low-cost energy at surplus should the wind and solar plans take longer to establish or not perform as expected.
Costs and Baskets of Eggs
Each of the four states named also have highly conducive political environments for business. California, love it or hate it, is one of the worst places in the nation to attempt to start a manufacturing business in terms of bureaucracy, costs, and red tape. Choosing California would also mean Tesla would be putting all of their eggs into one basket, as it were, geographically and politically. This would directly affect our next point. We’ll discuss that in a moment.
All four of the states listed have low or no corporate income tax, have relatively low property taxes (even for industrial use), and are about as business-friendly as a state’s government can be without giving away the farm. Nevada and Arizona also have corporate-friendly incorporation laws, should Tesla need to use them.
Leverage
Now for the real meat of it. Tesla has already leveraged California for about everything it can in terms of concessions and breaks. California would likely be willing to do a lot to help Musk get his Gigafactory built, but it’s just as likely that the other candidates would do just as much on top of their already-friendly atmosphere, industry-wise.
Further, two of these states (do we need to name them?) have been less than friendly to Tesla during the dealership vs direct sales battles. Dangle the “create a green factory and employ a lot of your citizens” carrot, though, and suddenly the discussion might begin to change a little.
You don’t have to be Richard Nixon to see that the prospect of one of the world’s largest automotive battery factories being located in your state will have a hundred benefits to every loss you might politically incur for turning your back on your friends at the auto dealer’s association. Especially if you’re a governor with hopes of getting into the White House (ahemRickPerryahem). It’s things like the Gigafactory that can build legacies for those with the savvy to utilize the PR potential.
Strategically Speaking
Putting it together, the strategy behind the Gigafactory’s geographic location is very astute. Musk and Co gain more by naming enemies in their list of potentials than they would going the relatively safe route of staying in their west coast comfort zone.
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
