From the Desk of Captain Obvious: How Image Recognition Mostly Works
July 8, 2019
Want to be reminded about how super duper image recognition systems work? If so, navigate to the capitalist’s tool “Facebook’s ALT Tags Remind Us That Deep Learning Still Sees Images as Keywords.” The DarkCyber teams knows that this headline is designed to capture clicks and certainly does not apply to every image recognition system available. But if the image is linked via metadata to something other than a numeric code, then images are indeed mapped to words. Words, it turns out, remain useful in our video and picture first world.
Nevertheless, the write up offers some interesting comments, which is what the DarkCyber research team expects from the capitalist tool. (One of our DarkCyber team saw Malcolm Forbes at a Manhattan eatery keeping a close eye on a spectacularly gaudy motorcycle. Alas, that Mr. Forbes is no longer with us, although the motorcycle probably survives somewhere unlike the “old” Forbes’ editorial policies.
Here’s the passage:
For all the hype and hyperbole about the AI revolution, today’s best deep learning content understanding algorithms are still remarkably primitive and brittle. In place of humans’ rich semantic understanding of imagery, production image recognition algorithms see images merely through predefined galleries of metadata tags they apply based on brittle and naïve correlative models that are trivially confused.
Yep, and ultimately the hundreds of millions of driver license pictures will be mapped to words; for example, name, address, city, state, zip, along with a helpful pointer to other data about the driver.
The capitalist tool reminds the patient reader:
Today’s deep learning algorithms “see” imagery by running it through a set of predefined models that look for simple surface-level correlative patterns in the arrangement of its pixels and output a list of subject tags much like those human catalogers half a century ago.
Once again, no push back from Harrod’s Creek. However, it is disappointing that new research is not referenced in the article; for example, the companies involved in Darpa Upside.
Stephen E Arnold, July 8, 2019
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