News
Tesla crash leads NTSB to begin probe of autonomous driving technology
The echoes of the Autopilot crash that killed Joshua Brown on May 7 are still reverberating. Not only is the National Highway Transportation Safety Administration conducting an investigation, now the National Transportation Safety Board (NTSB) is getting into the act. NHTSA chief Mark Rosekind and Transportation Secretary Anthony Fox have expressed approval of autonomous driving technology. With more than 80% of the 34,000 highway deaths in the US every year attributed to human error, they recognize the power of new safety system to reduce the carnage on America’s roadways.
The NTSB on the other hand has warned that such systems can lead to danger because they lull drivers into complacency behind the wheel. Missy Cummings, an engineering professor and human factors expert at Duke University, says humans tend to show “automation bias,” a trust that automated systems can handle all situations when they work 80% of the time.
According to Automotive News, NTSB will send a team of five investigators to Florida to probe the of Joshua Brown after his Tesla Model S while driving on Autopilot crashed into a tractor trailer. “It’s worth taking a look and seeing what we can learn from that event, so that as that automation is more widely introduced we can do it in the safest way possible,” says Christopher O’Neil, who heads the NTSB.
“It’s very significant,” says Clarence Ditlow, executive director of the Center for Auto Safety, an advocacy group in Washington, DC. “The NTSB only investigates crashes with broader implications.” He says the action by the NTSB is significant. “They’re not looking at just this crash. They’re looking at the broader aspects. Are these driverless vehicles safe? Are there enough regulations in place to ensure their safety” Ditlow adds, “And one thing in this crash I’m certain they’re going to look at is using the American public as test drivers for beta systems in vehicles. That is simply unheard of in auto safety,” he said.
That is the crux of the situation. Tesla obviously has the right to conduct a beta test of its Autopilot system if only other Tesla drivers were involved. The question is whether it has the same right to do so on public roads with other drivers who are not part of the beta test and who are unaware than an experiment is taking place around them as they drive?
For its part, Tesla steadfastly maintains that “Autopilot is by far the most advanced driver-assistance system on the road, but it does not turn a Tesla into an autonomous vehicle and does not allow the driver to abdicate responsibility. Since the release of Autopilot, we’ve continuously educated customers on the use of the feature, reminding them that they’re responsible for remaining alert and present when using Autopilot and must be prepared to take control at all times.”
That’s all well and good, but are such pronouncements from the company enough to overcome that “automation bias” Professor Cummings refers to? Clearly, Ditlow thinks not. What the NTSB decides to do, if anything, after it completes its investigation could have a dramatic impact on self driving technology both in the US and around the world. Regulators in other countries will place a lot of weight on what the Board decides.
From Tesla’s perspective, they will want to know if the death of one person is reason enough to delay implementation of technology that could save 100,000 or more lives each year worldwide. The company is racing ahead with improvements to its Autopilot system. Just the other week a Tesla Model S was spotted testing near the company’s Silicon Valley-based headquarters with a LIDAR mounted to its roof.
NTSB has a lot of clout when it comes to promulgating safety regulations. It will be hard pressed to fairly balance all of the competing interests involved in the aftermath of the Joshua Brown fatality.
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
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.
Investor's Corner
Tesla has one big financial question to answer for investors: Morgan Stanley
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.”
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.
Investor's Corner
SpaceX AI investment gamble will make it a big winner, firm says
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.
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.
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.
