Credit: Underwriters Laboratories
Google dazzled developers this week with a new feature called Google Lens.
Appearing first in Google Assistant and Google Photos, Google Lens uses artificial intelligence (A.I.) to specifically identify things in the frame of a smartphone camera.
In Google's demo, not only did Google Lens identify a flower, but the species of flower. The demo also showed the automatic login to a wireless router when Google Lens was pointed at the router barcodes. And finally, Google Lens was shown identifying businesses by sight, popping up Google Maps cards for each establishment.
Google Lens is shiny and fun. But from the resulting media commentary, it was clear that the real implications were generally lost.
The common reaction was: "Oooh, look! Another toy for our smartphones! Isn't A.I. amazing!" In reality, Google showed us a glimpse of the future of general-purpose sensing. Thanks to machine learning, it's now possible to create a million different sensors in software using only one actual sensor -- the camera.
In Google's demo, it's clear that the camera functions as a "super-sensor." Instead of a flower-identification sensor, a bar-code reader and a retail-business identifier, Google Lens is just one all-purpose super-sensor with software-based, A.I.-fueled "virtual sensors" built in software either locally or in the cloud.
Remember the 'trillion sensor world'?
Talking about the Internet of Things (IoT) four years ago, the phrase "trillion sensor world" came into vogue in IT circles. Futurists vaguely imagined a trillion tiny devices with a trillion antennas and a trillion batteries (that had to be changed a trillion times a year).
In this future, we would be covered in wearable sensors. All merchandise and machinery would be tagged with RFID chips that would alert mounted readers to their locations. Special purpose sensors would pervade our homes, offices and workplaces.
We were so innocent then -- mostly about the promise and coming ubiquity of A.I. and machine learning.
In the past four years, another revolution has disrupted the expected "trillion sensor world" revolution, namely the rise in cloud A.I., which changes everything. Instead of different, single-purpose sensors installed all over every vehicle, person, wall, machine and road, we'll have general-purpose super-sensors, and their data will be used for software-based virtual sensors.
Why 'synthetic sensors' are better than real ones
Researchers at Carnegie Mellon University (CMU) last week unveiled their "super sensor" technology, which they also call a "synthetic sensor."
Carnegie Mellon University researchers this month unveiled their super-sensor technology, which can detect just about anything happening on a factory floor. Credit: CMU
Despite the name, there are real sensors involved. The researchers have developed a board containing a small range of sensors commonly used in enterprise and commercial environments. The encased board functions like a single black-box sensor that plugs into a wall or USB power source and connects via Wi-Fi.
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