Questions continue to swirl around the fate of Tesla stock (NASDAQ:TSLA) as the market waits for updates about Elon Musk’s initiative to make the company private. Tesla’s privatization, provided that it does go through, will be the largest one in history, amounting to around $70 billion at Musk’s target of $420 per share. While this amount is substantial, $420 is actually a pretty good deal for Tesla’s would-be funding partners, considering the volume of Autopilot data the company has gathered from its Model S, Model X and Model 3 fleet.

Tesla’s possible privatization has caused wild swings in Tesla’s stock price, though not too far a departure from its usual volatility. Upon Musk’s announcement, shares climbed up 11%, before falling back as reservations emerged from critics about the plausibility of the company’s privatization. On Thursday’s after-hours, Tesla stock recovered some of its losses as the company’s board of directors issued a statement stating that they would formally review Musk’s plans.

Gene Munster, Managing Partner at Loup Ventures believes that there is more than a 50% chance that Tesla would become a private company. Munster noted that while concerns about the possible repercussions of Musk’s go-private Twitter announcement might affect the stock, the effects would only be felt at the very short-term. Ultimately, the venture capital firm believes that neither Tesla nor Elon Musk is at legal risk, especially since the company stated on a 2013 Form 8-K  that social media might be used as an outlet for disseminating company information. Loup Ventures also estimates that Tesla would need around $25-$30 billion to take the electric car and energy company private.

If Loup Ventures’ calculations prove accurate, the entities providing the company with the funding to go private would be getting quite a deal at $420 per share. Apart from Tesla’s electric car and energy business — both of which are growing at an immense rate — investors would also be buying into a company that holds what could very well be automotive world’s most extensive amount of real-world driving data. As of July, a report from MIT’s Lex Fridman estimated that Tesla had acquired around 1.2 billion miles on Autopilot and approximately 7.8 billion miles in Autopilot “Shadow Mode.”

In comparison, Waymo’s fleet of vehicles have driven a total of 5 million real-world miles in self-driving mode and an additional 5 billion miles in simulation as of May this year. GM Cruise, another leader in self-driving technology, does not release the numbers of its fleet, but accident and disengagement reports based on autonomous miles driven provide a rough estimate of the miles Cruise’s vehicles have traveled so far. Between June 2015 and November 2017, the California Department of Motor Vehicles estimated that GM Cruise’s self-driving cars covered a total of 141,691 miles in CA. Morgan Stanley analyst Adam Jonas estimates Waymo to be worth $175 billion. GM Cruise, on the other hand, is valued at $11.5 billion after securing more funding from Softbank’s Vision Fund earlier this year.

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Tesla’s development of self-driving technologies has taken a backseat in the media coverage of the company, particularly during the past year as the company struggled with the Model 3 ramp. Regardless of this, Keith Wright, a professor from Villanova University, notes that Elon Musk’s decision to invest heavily in AI would likely pay off soon. Among the participants in the self-driving race, Tesla is the company with the most real-world experience. Elon Musk once noted that it would likely take around 6 billion real-world miles before regulators would approve self-driving technology. So far, Tesla is the company closest to that mark.

Tesla’s focus on data gathered from real-world miles was emphasized by Nidhi Kalra, a senior information scientist for the RAND Corporation, a nonprofit research organization. According to the information scientist, simulations such as the ones used by Waymo to train its fleet of autonomous vehicles are a “simplification” of the real world.

“The problem with any simulator is that it’s a simplification of the real world. Even if it stimulates the world accurately, if all you’re simulating is a sunny day in Mountain View with no traffic, then what is the value of doing a billion miles on the same cul-de-sac in Mountain View? I’m not saying that’s what anyone’s doing but without that information we can’t know what a billion miles really means. Real-world miles still really, really matter. That’s where, literally, the rubber meets the road, and there’s no substitute for it,” Kalra said.

And Tesla is just getting started. In Tesla’s Q2 2018 earnings call, the company provided an update on its efforts to develop its own self-driving hardware. According to Pete Bannon, who leads the development of Hardware 3, the company’s new hardware is different from the industry standard.

“We did a survey of all of the solutions that were out there for running neural networks, including GPUs. We went and talked to other people like at ARM that were building embedded solutions for running neural networks. And pretty much everywhere we looked, if somebody had a hammer, whether it was a CPU or a GPU or whatever, they were adding something to accelerate neural networks. But nobody was doing a bottoms-up design from scratch, which is what we elected to do.”

“We had the benefit of having the insight into seeing what Tesla’s neural networks looked like back then and having projections of what they would look like into the future, and we were able to leverage all of that knowledge and our willingness to totally commit to that style of computing to produce a design that’s dramatically more efficient and has dramatically more performance than what you can buy today.”

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Tesla could very well be approaching its most significant turning point in years. Regardless of whether Tesla becomes private or not, one thing seems sure — once Tesla starts rolling out its first full self-driving features, and once Hardware 3 makes it to the company’s fleet, leaders in the self-driving industry would probably be forced to recognize the presence of a new, possibly dominant player.