Uber aims to leverage its millions of active drivers as a data collection infrastructure for autonomous vehicle development. CTO Praveen Neppalli Naga outlined the strategy as an expansion of the company's AV Labs initiative announced in January.
Uber intends to transform its driver network into a distributed sensor grid to support self-driving technology companies. The move represents a shift in how the ride-hailing company approaches autonomous vehicle development following years of struggles with its own self-driving division.
Neppalli Naga disclosed the plan during a presentation at TechCrunch's StrictlyVC conference in San Francisco Thursday. He framed the initiative as a natural progression of AV Labs, Uber's recently launched program focused on autonomous vehicle advancement.
The approach would essentially turn Uber's fleet of millions of drivers into mobile data collectors. Vehicles in the network would gather information through their existing sensors—cameras, lidar, and radar systems—providing real-world driving data across numerous geographies and conditions. This data collection could benefit multiple self-driving companies, creating a valuable resource for training and validating autonomous systems.
The strategy addresses a significant challenge in autonomous vehicle development: obtaining diverse, real-world training data at scale. Rather than investing heavily in proprietary sensor networks or relying on limited testing programs, Uber could monetize its existing infrastructure and driver base.
This pivot marks a notable change from Uber's previous autonomous vehicle efforts. The company shuttered its self-driving division in 2020 and sold its autonomous truck unit Advanced Technologies Group to Aurora Innovation. The new approach suggests Uber is positioning itself as a data provider and platform facilitator rather than a direct competitor in autonomous vehicle manufacturing.
The program could generate additional revenue streams for Uber while reducing capital expenditure on autonomous technology development. For autonomous vehicle companies, access to Uber's driver data would provide unprecedented scale and diversity for training algorithms.
Details regarding data sharing agreements, compensation structures, and privacy safeguards have not been disclosed. The initiative is expected to expand as AV Labs develops further.
X has updated its algorithm to prioritize replies from people you already follow in comment sections. The change gives followers' responses higher visibility in the reply feed.
KeyBanc Capital Markets downgraded Apple to underweight, delivering a rare bearish call on the tech giant. The firm cited demand risks and valuation concerns as key drivers.
IBM reported preliminary second-quarter sales below expectations, prompting CEO acknowledgment of underperformance. The company attributed the shortfall to customers prioritizing spending on chips and servers driven by AI demand.
UK Chancellor Rachel Reeves has instructed cabinet ministers to prioritize British companies for government procurement in ships, steel, energy, and AI. The directive comes amid frustration that too much public spending is going to foreign firms.