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For autonomous machines to flourish, scalability is everything

The University of Rochester's Yuhao Zhu says scaling autonomation development to relevant data is key to accelerating progress.

Mar 31, 2025

1 min

The past decade has seen remarkable advancements in robotics and AI technologies, ushering in the era of autonomous machines. While the rise of these machines promises to revolutionize our economy, the reality has fallen short of expectations.


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That’s not for a lack of intensive investments in research in development, says Yuhao Zhu, an associate professor of computer science at the University of Rochester.


The reason we’re not seeing more service robots, autonomous drones, and self-driving vehicles, Zhu says, is that autonomation development is currently scaling with the size of engineering teams rather than the amount of relevant data and computational resources.


This limitation prevents the autonomy industry from fully leveraging economies of scale, Zhu says, particularly the exponentially decreasing cost of computing power and the explosion of available data.


Zhu recently co-authored a report on the quest for economies of scale in autonomation in Communications of the ACM and is part of an international team of computer scientists focused on making autonomous machines more reliable and less costly. He can be reached by email at yzhu@rochester.edu.


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