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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.

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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.”

Source: Bloomberg   Photo credit: Uber, AP

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Elon Musk

Tesla’s Elon Musk: 10 billion miles needed for safe Unsupervised FSD

As per the CEO, roughly 10 billion miles of training data are required due to reality’s “super long tail of complexity.” 

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Credit: @BLKMDL3/X

Tesla CEO Elon Musk has provided an updated estimate for the training data needed to achieve truly safe unsupervised Full Self-Driving (FSD). 

As per the CEO, roughly 10 billion miles of training data are required due to reality’s “super long tail of complexity.” 

10 billion miles of training data

Musk comment came as a reply to Apple and Rivian alum Paul Beisel, who posted an analysis on X about the gap between tech demonstrations and real-world products. In his post, Beisel highlighted Tesla’s data-driven lead in autonomy, and he also argued that it would not be easy for rivals to become a legitimate competitor to FSD quickly. 

“The notion that someone can ‘catch up’ to this problem primarily through simulation and limited on-road exposure strikes me as deeply naive. This is not a demo problem. It is a scale, data, and iteration problem— and Tesla is already far, far down that road while others are just getting started,” Beisel wrote. 

Musk responded to Beisel’s post, stating that “Roughly 10 billion miles of training data is needed to achieve safe unsupervised self-driving. Reality has a super long tail of complexity.” This is quite interesting considering that in his Master Plan Part Deux, Elon Musk estimated that worldwide regulatory approval for autonomous driving would require around 6 billion miles. 

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FSD’s total training miles

As 2025 came to a close, Tesla community members observed that FSD was already nearing 7 billion miles driven, with over 2.5 billion miles being from inner city roads. The 7-billion-mile mark was passed just a few days later. This suggests that Tesla is likely the company today with the most training data for its autonomous driving program. 

The difficulties of achieving autonomy were referenced by Elon Musk recently, when he commented on Nvidia’s Alpamayo program. As per Musk, “they will find that it’s easy to get to 99% and then super hard to solve the long tail of the distribution.” These sentiments were echoed by Tesla VP for AI software Ashok Elluswamy, who also noted on X that “the long tail is sooo long, that most people can’t grasp it.”

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Tesla earns top honors at MotorTrend’s SDV Innovator Awards

MotorTrend’s SDV Awards were presented during CES 2026 in Las Vegas.

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Credit: Tesla China

Tesla emerged as one of the most recognized automakers at MotorTrend’s 2026 Software-Defined Vehicle (SDV) Innovator Awards.

As could be seen in a press release from the publication, two key Tesla employees were honored for their work on AI, autonomy, and vehicle software. MotorTrend’s SDV Awards were presented during CES 2026 in Las Vegas.

Tesla leaders and engineers recognized

The fourth annual SDV Innovator Awards celebrate pioneers and experts who are pushing the automotive industry deeper into software-driven development. Among the most notable honorees for this year was Ashok Elluswamy, Tesla’s Vice President of AI Software, who received a Pioneer Award for his role in advancing artificial intelligence and autonomy across the company’s vehicle lineup.

Tesla also secured recognition in the Expert category, with Lawson Fulton, a staff Autopilot machine learning engineer, honored for his contributions to Tesla’s driver-assistance and autonomous systems.

Tesla’s software-first strategy

While automakers like General Motors, Ford, and Rivian also received recognition, Tesla’s multiple awards stood out given the company’s outsized role in popularizing software-defined vehicles over the past decade. From frequent OTA updates to its data-driven approach to autonomy, Tesla has consistently treated vehicles as evolving software platforms rather than static products.

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This has made Tesla’s vehicles very unique in their respective sectors, as they are arguably the only cars that objectively get better over time. This is especially true for vehicles that are loaded with the company’s Full Self-Driving system, which are getting progressively more intelligent and autonomous over time. The majority of Tesla’s updates to its vehicles are free as well, which is very much appreciated by customers worldwide.

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Elon Musk

Judge clears path for Elon Musk’s OpenAI lawsuit to go before a jury

The decision maintains Musk’s claims that OpenAI’s shift toward a for-profit structure violated early assurances made to him as a co-founder.

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Gage Skidmore, CC BY-SA 4.0 , via Wikimedia Commons

A U.S. judge has ruled that Elon Musk’s lawsuit accusing OpenAI of abandoning its founding nonprofit mission can proceed to a jury trial. 

The decision maintains Musk’s claims that OpenAI’s shift toward a for-profit structure violated early assurances made to him as a co-founder. These claims are directly opposed by OpenAI.

Judge says disputed facts warrant a trial

At a hearing in Oakland, U.S. District Judge Yvonne Gonzalez Rogers stated that there was “plenty of evidence” suggesting that OpenAI leaders had promised that the organization’s original nonprofit structure would be maintained. She ruled that those disputed facts should be evaluated by a jury at a trial in March rather than decided by the court at this stage, as noted in a Reuters report.

Musk helped co-found OpenAI in 2015 but left the organization in 2018. In his lawsuit, he argued that he contributed roughly $38 million, or about 60% of OpenAI’s early funding, based on assurances that the company would remain a nonprofit dedicated to the public benefit. He is seeking unspecified monetary damages tied to what he describes as “ill-gotten gains.”

OpenAI, however, has repeatedly rejected Musk’s allegations. The company has stated that Musk’s claims were baseless and part of a pattern of harassment.

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Rivalries and Microsoft ties

The case unfolds against the backdrop of intensifying competition in generative artificial intelligence. Musk now runs xAI, whose Grok chatbot competes directly with OpenAI’s flagship ChatGPT. OpenAI has argued that Musk is a frustrated commercial rival who is simply attempting to slow down a market leader.

The lawsuit also names Microsoft as a defendant, citing its multibillion-dollar partnerships with OpenAI. Microsoft has urged the court to dismiss the claims against it, arguing there is no evidence it aided or abetted any alleged misconduct. Lawyers for OpenAI have also pushed for the case to be thrown out, claiming that Musk failed to show sufficient factual basis for claims such as fraud and breach of contract.

Judge Gonzalez Rogers, however, declined to end the case at this stage, noting that a jury would also need to consider whether Musk filed the lawsuit within the applicable statute of limitations. Still, the dispute between Elon Musk and OpenAI is now headed for a high-profile jury trial in the coming months.

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