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How consumers view robotaxis ahead of Tesla’s ‘We, Robot’ event: study
Ahead of Tesla’s Robotaxi unveiling event on Thursday, one firm has released data suggesting that early consumer experience with driverless ride-hailing platforms has generally been positive.
On Tuesday, J.D. Power shared the results of its 2024 U.S. Robotaxi Experience study, which found that, on average, consumers ranked driverless ride-hailing experiences an 8.53 out of 10. In its second year, the study surveyed 3,773 respondents along with 773 consumers who lived in cities such as San Francisco, Los Angeles, Phoenix, Las Vegas, and Dallas, where robotaxi services are already available.
Perhaps unsurprisingly, consumer confidence in robotaxis was about substantially higher in those who had prior experience in one of the self-driving vehicles, landing at 76 percent, and well above the 20 percent for those who had not. Consumer confidence was also improved by public exposure to the technology, with 34 percent of those who had not ridden but had witnessed self-driving vehicles expressing some level of trust and acceptance.
Notably, these results suggest that sheer experience with robotaxi platforms — both riding inside them and seeing them on the street — tends to give consumers greater public trust in these driverless solutions. The results also come as the market for driverless ride-hailing continues to grow, as Tesla and other companies ready their commercial robotaxi offerings.
The study featured five categories, including comfort and convenience, initiating rides, taking rides in the given vehicle, service availability and cost, as well as overall vehicle technology. Responses for the study were fielded in August.
What's special about FSD Supervised is that it works anywhere in the US & Canada.
No high definition maps, no geofence.
This means you can even use it in places that no Tesla has never traveled to before
— Tesla AI (@Tesla_AI) October 4, 2024
The key findings also included that consumers regularly seek out safety features and easy access to authorities, such as the inclusion of an emergency button in robotaxis. Service area coverage and cost remain barriers for some consumers who haven’t tried the services out yet, with the vast majority of companies employing a mapping strategy to certain service areas.
“The robotaxi segment is still anyone’s game, given that most people are not familiar with robotaxi brands and haven’t formed a clear associative imagery,” said Kathleen Rizk, J.D. Power’s Senior Director of User Experience Benchmarking and Technology.
Other key findings include that consumers strongly value how well vehicles navigate traffic laws, and how well they perform when maneuvering regular traffic. In addition, 77 percent of rides said they would prefer a driverless robotaxi to a ride-share with a human driver when needing to have a private conversation.
You can view J.D. Power’s full study results for the 2024 Robotaxi Experience Study on the firm’s website here.
Currently, driverless ride-hailing services and tests are operated by the Google-owned company Waymo, May Mobility, Zoox, and Motional. Meanwhile, General Motors (GM) subsidiary Cruise was forced to halt self-driving operations last fall after an accident with a pedestrian, though it’s currently aiming to relaunch services by the end of this year.
While Tesla offers its Full Self-Driving (FSD) Supervised to customers, it doesn’t currently have the software available to consumers as a driverless ride-hailing system. However, the company is widely expected to unveil a ride-hailing service during its “We, Robot” event on Thursday, and it has already teased a mobile app ride-hailing platform.
The company’s FSD Supervised, eventually expected to become Unsupervised as Tesla targets the cars becoming safer than human drivers, is also one of the only self-driving softwares out there that doesn’t utilize area mapping. For that reason, Tesla has touted its ability to scale FSD beyond mapped-out service areas, especially when paired with the ongoing training of its AI neural network through real-time driving footage.
Apparent camouflaged Tesla Robotaxi prototype sighted at Warner Bros. Burbank
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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.”
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.
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.
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.
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.
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.
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.
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.