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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.

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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.”

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.”

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Source: Bloomberg   Photo credit: Uber, AP

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Elon Musk dispels $52 billion SpaceX-NVIDIA GPU deal: ‘Fake news’

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Credit: SpaceX

Elon Musk dismissed reports claiming SpaceX had placed a massive order for NVIDIA GPUs worth $52 billion. The denial came hours after Taiwanese media, citing unnamed industry sources, reported that SpaceX planned to acquire approximately 13,000 AI server racks, equating to roughly 1 million GB300 GPUs, from Foxconn.

Each rack was estimated at around $4 million, with deliveries potentially starting in late 2025.

The story suggested this would mark SpaceX’s first major foray into Foxconn-manufactured NVIDIA hardware, breaking from suppliers like Supermicro and Dell. Musk responded bluntly on X:

Despite the denial, the rumored scale aligns with SpaceX’s explosive growth in AI infrastructure. NVIDIA’s GB300 (successor to the GB200 NVL) racks deliver unprecedented performance for large-scale training and inference. A $52 billion commitment would dwarf most corporate AI budgets and provide the compute muscle needed for frontier models.

SpaceX already operates gigawatt-scale terrestrial clusters like Colossus in Memphis, Tennessee, and has monetized them aggressively through leasing deals.

SpaceX’s newest Starmind will make earth data centers obsolete

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Major customers include Anthropic (paying ~$1.25 billion monthly for 220,000+ GPUs), Google (~$920 million monthly for 110,000 GPUs), and Reflection AI. These arrangements are projected to generate tens of billions in annual revenue, far outpacing traditional SpaceX businesses.

Such an investment would fuel internal AI efforts, particularly Grok models under the integrated SpaceXAI division, while supporting ambitious orbital data center plans. SpaceX envisions launching thousands of AI-optimized satellites powered by solar energy and cooled in space, bypassing terrestrial power and land constraints.

This “Starmind” constellation could position the company as a leader in space-based computing.

SpaceX as an Emerging AI Powerhouse

Once primarily known for reusable rockets and Starlink satellite internet, SpaceX has transformed into a multifaceted AI player.

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The 2026 acquisition of xAI integrated Grok development directly into the company. Starlink’s low-latency global network complements massive compute clusters, enabling efficient data flow for training and serving AI models.

Musk has long argued that AI scaling demands solutions beyond Earth, citing things like real estate and electricity limits on the ground.

While the Foxconn deal may not be in the cards, SpaceX’s trajectory is continuing on the path of blending aerospace engineering with hyperscale AI to dominate both launches and intelligence infrastructure.

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Elon Musk sheds details on Tesla FSD’s upcoming improvements

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Credit: Tesla

Elon Musk shed more details on the upcoming improvements to Tesla’s Full Self-Driving suite, specifically one that the CEO mentioned last week, which should help owners see fewer interventions.

Last week, Musk hinted that one major improvement that Tesla planned to roll out to Full Self-Driving users was the car’s ability “to remember your specific interventions and match each person’s individual preferences.”

Elon Musk says your Tesla will start to learn your individual preferences

This small bit of detail was linked to a post from Tesla community member Whole Mars, who said that FSD’s tendency to exit the carpool lane, a feature that owners can turn on but at times the car will disregard.

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It sounds like, based on Musk’s two responses since that original post, it is safe to say the things FSD will start to remember are wide-ranging. However, it seems the biggest differences will be noticed with parking performance, which Musk continues to mention.

Highway Lane Preferences

The initial post Musk mentioned, with these new remembered preferences soon to arrive for Tesla owners everywhere, was the Carpool/Express Lane.

Tesla has a setting in the FSD menu that lets drivers enable HOV Lane travel. However, the car won’t always stay in that suggested or preferred lane.

Some owners have also complained of left lane camping, an illegal maneuver in at least some states. Cruising in the passing lane has resulted in tickets for some, as it is illegal in over 30 states in the U.S.

Tesla did not confirm if these preferences would also be included in new FSD behaviors, but it would certainly help move the company toward fewer interventions.

Parking Preferences

This seems to be the real focus of the entire operation, as Musk stated several weeks ago that parking was overwhelmingly the most frequent reason for interventions.

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The major issue with parking is not necessarily the parking “performance,” as FSD is generally good at parking. It definitely has its issues; we’ve recorded plenty of them, including this one as recent as last week:

However, the changes coming are more about preferences, meaning where you park and how your car enters the spot, either pulling in or backing in. Owners have also reported that pulling into the correct driveway is a relatively rare thing for FSD, something else that needs to be confronted.

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Musk basically confirmed that all of these things would be part of Tesla’s plan to address driver preferences with FSD:

It’s obvious there is something big coming with FSD, and the company’s focus seems to be eliminating any intervention that would be related to preferences. This is probably the biggest bottleneck between Tesla and being fully autonomous. Critical interventions do occur, but they are much less frequent.

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The only time a driver should be taking over is because of a critical intervention; this seems to be the goal of Tesla right now.

This all seems to be a priority as Tesla continues to move closer to the prospect of unsupervised driving.

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Elon Musk says your Tesla will start to learn your individual preferences

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Credit: Tesla

Elon Musk said today on X that Teslas will start to learn your individual preferences. This is something that he seemed to hint toward earlier this month when he said parking was by far the biggest reason drivers intervene with Full Self-Driving.

Musk made the comment in response to notable Tesla influencer Whole Mars, who said that his vehicle will sometimes disobey the settings he has enabled for his car. He responded to the post, stating that “The car will start to remember your specific interventions and match each person’s individual preferences.”

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This is something that could be perhaps one of the biggest ways Tesla could minimize or even work closer toward eliminating interventions altogether. While FSD does a lot of things really well, many people intervene a vast majority of the time not due to major or critical safety errors.

Instead, many take over because the car is doing something that they do not like as a preference; it might park in a parking spot that is not preferred by the driver, it might linger too long in the left lane on the highway (a personal favorite), or it could even take a route that the driver does not like.

These all lead to interventions, but they are not triggered by a major safety issue. Instead, it’s just preference.

READ OUR REVIEW OF TESLA’S LATEST FSD VERSION:

Tesla Full Self-Driving v14.3.5 Early Impressions: new features and early performance

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If Teslas could start to learn the personal preferences of the person who owns them, interventions will truly begin to be less frequent. Some of this is already pretty evident, in my opinion. Teslas use a neural network to learn behaviors and accumulate data to improve performance.

For months now, we’ve tracked FSD’s performance at “Except Right Turn” stop signs, something that is very common in Pennsylvania, but many of our readers located in other parts of the U.S. have never heard of. FSD handles one Except Right Turn stop sign very well, one that I travel past frequently. Others that I do not navigate through as often do not have as confident a performance. It seems like the cars might already be doing this to an extent.

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That example is also for something that is a street sign and not necessarily a driver preference; however, I still feel it is worth mentioning because it only handles that commonly passed Except Right Turn stop sign with true confidence. Others it still seems to struggle with.

This could be one of Tesla’s big moves toward full autonomy, and it could be a pathway to truly unsupervised driving. Every day, millions of cars on the road travel at a human driver’s personal preferences with no incident. Why can’t autonomous vehicles still cater to a passenger’s preferences while being autonomous? Tesla seems to have the idea that it would be possible.

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