Uber's Ambitious Plan to Become the Data Layer for the AV Ecosystem
Uber has a long-term ambition to turn its millions of drivers into a sensor grid for self-driving companies, potentially creating a new revenue stream and cementing its position in the industry.
Uber's chief technology officer, Praveen Neppalli Naga, revealed the plan at TechCrunch's StrictlyVC event in San Francisco, describing it as a natural extension of the company's nascent program, AV Labs.
For now, AV Labs relies on a small, dedicated fleet of sensor-equipped cars that Uber operates itself, separate from its driver network. However, the ambition is clearly much larger, with Uber aiming to equip human drivers' vehicles with sensors to collect data for autonomous vehicle companies.
"The bottleneck is data," Naga said. "[Companies like Waymo] need to go around and collect the data, collect different scenarios. You may be able to say: In San Francisco, ‘At this school intersection, I want some data at this time of day so I can train my models.' The problem for all these companies is access to that data, because they don't have the capital to deploy the cars and go collect all this information."
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.
The company currently has partnerships with 25 AV companies and is building what Naga described as an "AV cloud": a library of labeled sensor data that partner companies can query and use to train their models.
"Our goal is not to make money out of this data," Naga said. "We want to democratize it."
However, given the obvious commercial value of what Uber is building, that positioning may not last long.
The company has already made equity investments 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's ride marketplace to reach customers.
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The Benefits of Uber's Plan
- Creating a new revenue stream for the company
- Cementing Uber's position in the industry
- Democratizing access to data for autonomous vehicle companies
The Challenges Ahead
- Regulatory hurdles
- Ensuring data quality and integrity
- Balancing the needs of multiple stakeholders
Conclusion
Uber's plan to turn its millions of drivers into a sensor grid for self-driving companies is a bold and ambitious move that could have significant implications for the industry. While there are challenges ahead, the benefits of this plan make it a compelling strategy for the company's future growth and success.