Investor's Corner
Tesla at $420 is a bargain considering its Autopilot data is key to a self-driving future
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.
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.
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“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.”
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.
Disclosure: I have no ownership in shares of TSLA and have no plans to initiate any positions within 72 hours.
Elon Musk
SpaceX’s next trillion dollar bet has nothing to do with rockets, Musk tells staff
Elon Musk told SpaceX staff AI revenue will soon dwarf rockets and Starlink combined entirely.
Elon Musk told SpaceX employees this week that artificial intelligence, not rockets, will soon carry the company’s revenue. In a roughly 29 minute internal address posted on SpaceX’s X account on Tuesday, Musk said AI revenue will pass every other line of business at SpaceX “probably in September” and pull further ahead by the fourth quarter.
The numbers he gave are specific. SpaceX currently runs 1.4 gigawatts of AI compute capacity. Musk wants that at 10 gigawatts by the end of 2027, a jump he tied directly to revenue: “if we bring 10GW of AI online by the end of next year, it will be $300 billion to $500 billion a year in revenue.” He called those “big numbers,” which undersells a projection larger than what most countries produce in a year.
We made rockets reusable and are rebuilding the internet in space. The next challenge: making life multiplanetary and understanding the true nature of the universe
Watch @ElonMusk deliver a company update to @SpaceX employees pic.twitter.com/5c8rxoCQfu
— SpaceX (@SpaceX) August 11, 2026
Musk went further on where AI fits into SpaceX’s future. “Probably in four or five years, AI will be 99% of the value of SpaceX,” he told staff, adding that digital intelligence would eventually run “a trillion times” ahead of biological intelligence as computing scales. He tied that growth to the company’s founding mission, telling employees “we must win on AI, because the future is overwhelmingly AI and robots,” with the payoff meant to help fund Starship and a Mars program that increasingly runs through Terafab, the joint Tesla, SpaceX and xAI chip plant.
Elon Musk launches TERAFAB: The $25B Tesla-SpaceXAI chip factory that will rewire the AI industry
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None of this is entirely new territory. SpaceX told investors much the same story during its first earnings call as a public company on August 4, where Musk moved the company’s $1 trillion revenue target up a year to 2030 and said Starlink could someday carry a majority of the world’s internet. What the all hands video adds is a hard deadline and a specific power figure Musk had not given publicly before, along with a franker pitch to his own workforce that AI, not launch cadence, is now the thing SpaceX is betting its future on.
The AI revenue itself is not coming from SpaceX training its own models. It is largely Starlink acting as the network layer for xAI’s workloads, plus SpaceX renting out compute capacity directly, the same approach behind the roughly $16 billion the company spent on AI infrastructure in a single quarter.
Musk closed the video with a pitch aimed at recruiting and retention rather than investors, telling employees that anyone who helps SpaceX win the AI race will eventually get the chance to go to the moon or Mars themselves. Whether SpaceX can turn 1.4 gigawatts into 10 in seventeen months is the more immediate question, and one that will show up in quarterly numbers well before anyone leaves Earth.
In a new note to investors on Tuesday, Morgan Stanley analyst Andrew Percoco said that Tesla has one big financial question to answer for investors regarding its Robotaxi rollout, Full Self-Driving software, and Optimus.
Percoco said in the note that, for the most part, investors are still very positive about the direction the company is headed. However, there are some things the firm would like to see, and they have to do with financials.
Tesla (TSLA) Q2 2026 earnings results: miss on EPS, beat on revenue
Tesla bulls are more than convinced that the company’s Full Self-Driving software is proof it can develop physical AI. Financially, however, there are still some questions, especially on elevated spending, which CEO Elon Musk said would occur as the company works to roll out Robotaxi faster and continue developing its Optimus robot.
The latter two are where Tesla will have to prove progress to investors, as Percoco writes that both projects “will require clearer evidence that Robotaxi is scaling and more tangible Optimus proof points to support the ROI on elevated capex.”
Percoco said the second quarter earnings call did not change his long-term thesis of where Tesla is positioned in the AI race, which is out in front. However, there are concerns that weaker gross margins and higher R&D spend will stress financials, and that has “sharpened our (and investors’) focus on measurable progress across Robotaxi and Optimus.”
Additionally, Robotaxi still needs to be proven with more operation in existing cities while maintaining safety but improving how many rides it gives in any given time, he said. For Optimus, Percoco wrote that he is “still looking for evidence beyond commentary around SOP.”
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Morgan Stanley put Percoco in charge of covering Tesla after long-time analyst Adam Jonas transitioned to the automotive side.
Currently, Morgan Stanley has a $415 price target on Tesla and a ‘Hold’ rating on the stock. It is trading at around $330 at the time of publication, which was 2:30 P.M. on the East Coast.
SpaceX’s massive investment in AI will make it a big winner, Argus Research said after the company’s successful earnings call last week.
The firm also upgraded shares to a Buy from Hold and set a $160 price target.
SpaceX (NASDAQ: SPCX) is currently recovering from its heavy AI infrastructure investments, as it spent nearly $16 billion in Q2 alone. The company did this primarily by monetizing high-demand GPU compute capacity at a much faster pace than traditional data center economics would suggest.
Company CFO Bret Johnsen said that SpaceX would be able to pay back anything on new deployments within a year.
There are plenty of ways the company can do this:
Leasing excess compute capacity through contracts
SpaceX has already built Colossus and Colossus II, largely for its own model training. However, much of that capacity is already rented out to third parties. It already has major deals with Anthropic, Google, and Reflection AI. These partnerships are adding billions per month to SpaceX’s spreadsheet.
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High utilization driven by industry-wide scarcity
The demand for advanced AI training and inference capacity continues to exceed what is available for use. SpaceX can fill new racks quickly after they come online, so the capital deployed converts into revenue with minimal idle time.
Additionally, management and outside observers have described the new compute capital as behaving more like a cost-of-goods-sold than traditional multi-year capex, especially because of this rapid monetization pattern.
Capacity has already scaled from ~0.4 GW a year to 1.4 GW annually by the end of Q2. There are targets of more than 2 GW by year-end.
High incremental margins on the rental business once capacity is online
GPU cloud providers often operate at strong gross margins. SpaceX can monetize capacity that was already partially built or can be added efficiently. This means that incremental EBITDA margins on the rental revenue are usually high. This accelerates cash recovery relative to the gross capital outlay.
Parallel monetization of its own AI software and applications
Beyond pure infrastructure rental, SpaceX also generates revenue from Grok through subscriptions and usage, from X through ads, data, and other related services, enterprise APIs, and the planned integration of the Cursor coding tools acquisition.
These application layers ride on the same compute infrastructure and provide additional high-margin streams that could offset build-out costs. AI-segment revenue overall rose sharply to about $2.6 billion in Q2, according to Motley Fool. This was driven primarily by the infrastructure contracts, but the software side is also partially responsible.
Efficient, large-scale deployment and vertical integration advantages
SpaceX has emphasized the rapid construction of power and cooling infrastructure and favorable cost-per-megawatt economics relative to industry benchmarks in some disclosures.
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Combined with its ability to scale capacity aggressively and the fact that many contracts start generating revenue within months of capacity coming online, the effective payback compresses dramatically compared with more conventional multi-year data-center projects.
SpaceX’s dominant near-term recovery path will turn the AI clusters into a hyperscale-style compute rental business for other leading AI companies while still using a portion for internal models.
SpaceX’s next trillion dollar bet has nothing to do with rockets, Musk tells staff
Tesla has one big financial question to answer for investors: Morgan Stanley
