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Uber has a long-term ambition that goes well beyond shuttling passengers: the company eventually wants to outfit its human drivers\u2019 cars with sensors to soak up real-world data for autonomous vehicle (AV) companies \u2014 and potentially other companies training AI models on physical-world scenarios.<\/p>\n
Praveen Neppalli Naga, Uber\u2019s chief technology officer, revealed the plan in an interview at TechCrunch\u2019s StrictlyVC event<\/a> in San Francisco on Thursday night, describing it as a natural extension of a nascent program the company announced in late January called AV Labs<\/a>.<\/p>\n \u201cThat is the direction we want to go eventually,\u201d Naga said of equipping human drivers\u2019 vehicles. \u201cBut first we need to get the understanding of the sensor kits and how they all work. There are some regulations \u2014 we have to make sure every state has [clarity on] what sensors mean, and what sharing it means.\u201d<\/p>\n For now, AV Labs relies on a small, dedicated fleet of sensor-equipped cars that Uber operates itself, separate from its driver network. But the ambition is clearly much larger. Uber has millions of drivers<\/a> globally, and if even a fraction of those cars could be transformed into rolling data-collection platforms, the scale of what Uber could offer the AV industry would dwarf what any individual AV company could assemble on its own.<\/p>\n The insight driving the program, Naga said, is that the limiting factor for AV development is no longer the underlying technology. \u201cThe bottleneck is data,\u201d he said. \u201c[Companies like Waymo] need to go around and collect the data, collect different scenarios. You may be able to say: in San Francisco, \u2018At this school intersection, I want some data at this time of day so I can train my models.\u2019 The problem for all these companies is access to that data, because they don\u2019t have the capital to deploy the cars and go collect all this information.\u201d<\/p>\n Becoming the data layer for the entire AV ecosystem is a pretty smart play, particularly considering Uber years ago abandoned its own ambitions to build self-driving cars (a move that co-founder Travis Kalanick has publicly lamented as a big mistake<\/a>). Indeed, many industry observers have wondered if, without its own self-driving cars, Uber might one day be rendered irrelevant as AVs increasingly spring up around the globe. <\/p>\n The company currently has partnerships with 25 AV companies \u2014 including Wayve, which operates in London \u2014 and is building what Naga described as an \u201cAV cloud\u201d: a library of labeled sensor data that partner companies can query and use to train their models. Partners, which Uber plans to more aggressively invest in directly<\/a>, can also use the system to run their trained models in \u201cshadow mode\u201d against real Uber trips, simulating how an AV would have performed without actually putting one on the road.<\/p>\n Techcrunch event<\/p>\n \n\t\t\t\t\t\t\t\t\tSan Francisco, CA<\/span> \u201cOur goal is not to make money out of this data,\u201d Naga said. \u201cWe want to democratize it.\u201d<\/p>\n Given the obvious commercial value of what Uber is building, that positioning may not last long. The company has already made equity investments<\/a> in numerous AV players, and its ability to offer proprietary training data at scale could give it significant leverage over a sector that right now depends on Uber\u2019s ride marketplace to reach customers.<\/p>\n<\/div>\n When you purchase through links in our articles, we may earn a small commission<\/a>. This doesn\u2019t affect our editorial independence.<\/em><\/p>\n
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\n\t\t\t\t\t\t\t\t\t\t\t\t\tOctober 13-15, 2026<\/span>\n\t\t\t\t\t\t\t<\/p>\n<\/p><\/div>\n<\/p><\/div>\n<\/div>\n