News
Tesla argues human error caused fatal 2019 crash, not Autopilot: report
Tesla now faces the jury’s verdict in a trial alleging that Autopilot caused a fatality, and the trial is expected to set a precedent for future cases surrounding advanced driver assistance systems (ADAS). During closing arguments on Tuesday, an attorney for the plaintiffs pointed to an analysis Tesla conducted two years before the accident, claiming that the automaker knowingly sold the Model 3 with a safety issue related to its steering.
The trial began in California late last month after a 2019 incident in which 37-year-old Micah Lee veered off a highway outside Los Angeles at 65 miles per hour, suddenly striking a palm tree before the vehicle burst into flames. According to court documents, the crash killed Lee and injured both of his passengers, one of whom was an 8-year-old boy.
Lee’s passengers and estate initiated a civil lawsuit against Tesla, alleging that the company knew that Autopilot and its other safety systems were defective when it sold the Model 3.
Tesla has denied any liability in the accident, claiming that Lee had consumed alcohol before getting behind the wheel and saying it could not detect if Autopilot was engaged at the time of the crash.
This and other trials come as regulatory requirements for ADAS suites are just emerging, and the cases are expected to help navigate future court cases related to accidents with the systems.
According to Reuters, the attorney for the plaintiffs, Jonathan Michaels, showed the jury an internal safety analysis from Tesla in 2017 during closing arguments, in which employees identified “incorrect steering command” as a potential safety issue. Michaels said the issue involved an “excessive” steering wheel angle, arguing that Tesla was aware of related safety problems before selling the Model 3.
“They predicted this was going to happen. They knew about it. They named it,” Michaels said.
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Michaels also said that Tesla created a specific protocol to deal with affected customers and that the company instructed workers to avoid accepting liability for the issue. Michaels also echoed prior arguments, saying that Tesla knew it was releasing Autopilot in an experimental state, though it needed to do so to boost market share.
“They had no regard for the loss of life,” Michaels added.
Michael Carey, Tesla’s attorney, said that the 2017 analysis wasn’t meant to identify the defect but instead was meant to help avoid any potential safety issues that could theoretically occur. Carey also said that Tesla developed a system to prevent Autopilot from making the same turn that had caused the crash.
Carey said that the subsequent development of the safety system “is a brick wall standing in the way of plaintiffs’ claim,” adding that there haven’t been any other cases where a Tesla has maneuvered the way that Lee’s did.
Instead, Carey argued to the jury that the crash’s simplest explanation was human error, asking jurors to avoid awarding damages on behalf of the severe injuries encountered by the victims.
“Empathy is a real thing, we’re not saying its not,” Carey argued. “But it does not make cars defective.”
Earlier this month, a federal judge in California ruled in Tesla’s favor in a similar case looking at whether the automaker misled consumers about its Autopilot system’s capabilities. In that case, which had the chance to become a class-action lawsuit, the judge ruled that most of the involved plaintiffs had signed an arbitration clause when purchasing the vehicle, requiring the claims to be settled outside of court.
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The cases are expected to set precedents in court for future trials involving Tesla’s Autopilot and Full Self-Driving (FSD) beta systems and the degree of the automaker’s responsibility in accidents related to their engagement. Tesla is also facing additional information requests from the U.S. Department of Justice related to its Autopilot and FSD beta.
Tesla has received more requests regarding Autopilot and FSD from DOJ
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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
