Processing power is an essential part to achieving the next level of technology in areas such as computer vision. When computer vision matures, drone package delivery, driverless cars and smart security systems will benefit.
In 2010, I attended the IEEE (Institute of Electrical and Electronics Engineers) CVPR (Computer Vision and Pattern Recognition) conference at the Hyatt in downtown San Francisco. I didn't expect the conference to be as large as it was, but it had more than 1,500 in attendance, to the best of my recollection. The conference reminded me of the size of the conferences held at the same hotel when the industry was arguing over different standards for Wi-Fi, with multi-billion dollar markets at stake.
However, unlike the practical approach of implementing the maturing Wi-Fi technology, where presentations were mainly made by engineers working for companies competing over their ability to assert their intellectual rights into the standards, the CVPR presentations were mainly made by university researchers, and researchers from "deep-research" arms of some of the world's largest technology companies, who didn't expect the fruit of their research to reach maturity anytime soon.
One of the presentations I sat through struck a chord with me. The presenter showed a 30-second video taken from a dash camera. As a speed limit sign appeared in the field of view, the program identified it, extracted the speed limit information from it, and displayed it to warn the driver. That was one of the coolest things I ever saw. To that point, I would rely on my own eyes to see those signs, and if I missed them--I could look at the navigation system which, typically, would show the speed limit known in the database. Of course, the navigation system's speed limit data could be outdated, or simply inaccurate. I'm sure that telling a Police officer, who stopped you for speeding, that the GPS said the speed limit was 40, where in reality it was 30, would not get you off the hook for a ticket.
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