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Uber will offer self-driving Volvos in Pittsburgh this month

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Uber customers in Pittsburgh who request a ride from the ride sharing service may find themselves riding in a specially prepared Volvo XC90 that can drive itself. Passengers will ride in a self-driving vehicle chaperoned by a human driver behind the wheel ready to take control of the car if necessary and an engineer monitoring the operation of the autonomous system. This will mark the first time a self-driving car has been used in commercial service in the United States.

Uber’s self-driving car program has been under the stewardship of John Bares since January, 2015. Bares was head of Carnegie Mellon University’s National Robotics Engineering Center for 13 years before he left to start Carnegie Robotics, a Pittsburgh-based company that makes components for self-driving industrial robots used in mining, farming, and the military.

“I turned him [Kalanick] down three times. But the case was pretty compelling.” Bares says. Once he joined Uber, he quickly put together a team consisting of hundreds of engineers, robotics experts, and few old fashioned auto mechanics. The mission was nothing less that to replace Uber’s 1 million human drivers with robotic drivers as soon as possible. The message is, if you drive for Uber, you should keep your resumé up to date and your eyes open for other lines of work.

Pittsburgh is the center of the Uber self-driving experiment because that is where the talent is. Carnegie Mellon is a world leader in autonomous systems. Its graduates are working on the Google car and are in high demand at any company planning to offer self-driving cars, including Apple and Tesla. Earlier in the year, a Tesla Model S loaded with cameras and sensors, presumably a test mule for Autopilot 2.0, was spotted testing in Pittsburgh.

So far, Uber has just a few specially modified Volvo XC90s ready for commercial service, but it expects to have 100 of them by the end of the year. The hardware at the heart of its self-driving system includes cameras, radar, lidar, GPS receivers, and a liquid cooled computer mounted in the rear.

Uber self driving Volvo

Uber self-driving Volvo XC90

Uber is moving fast. “We are going commercial,” says CEO Travis Kalanick. “This can’t just be about science.” Last month, it purchased Otto, a start-up company that is working to bring self-driving long haul trucks to market. In theory, its technology will allow truck drivers to crawl in back and nap while the trucks are on the highway. Uber will take over and re-brand that business and incorporate the Otto technology into its own self-driving systems.

Otto’s founders were all previously members of the Google car program, but grew impatient with the slow, plodding pace of development at Google. They wanted an opportunity to showcase their talents much sooner than they could if they remained at Google. “We were really excited about building something that could be launched early,” says Anthony Levandowski, co-founder of Otto.

Kalanick is clearly looking to be the first to begin offering a self-driving ride hailing service. He intends to beat Tesla, Apple, Google, Ford, and Genera Motors to the punch. “Nobody has set up software that can reliably drive a car safely without a human,” he says in an oblique reference to Tesla’s Autopilot system. “We are focusing on that.” Developing an autonomous vehicle, he adds, “is basically existential for us.”

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At first, trips in the self-driving Volvos will be free. Uber’s standard local rate is $1.30 per mile but Kalanick says eventually prices will be so low that the cost per mile will be cheaper in a self-driving Uber than in a private car, even in rural areas. “That could be seen as a threat,” says Volvo CEO Hakan Samuelsson. “We see it as an opportunity.”

Source: Bloomberg   Photo credit: Uber, AP

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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.

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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.

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.

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Investor's Corner

Tesla has one big financial question to answer for investors: Morgan Stanley

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Credit: Tesla

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.

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Investor's Corner

SpaceX AI investment gamble will make it a big winner, firm says

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Credit: SpaceX

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.

SpaceX is charging Anthropic massive money for its compute

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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.

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