Translation (Google translate, DeepL)
Automatically generated product descriptions, sometimes also edited by humans (Alibaba)
Image Tagging (Facebook photos)
Today, I've received a package from Amazon containing router bits (for wood working not IT). It contains a so called "User Manual" which is obviously so badly translated, I assume automatically, that it will only fool a spell checker, that it is actually written in German.
I often hear and read good things about Google Translate but every time I read something from it, e.g. when a browser or webpage helpfully decides that I would prefer a butchered salad of German words instead of an English web page, I am repulsed.
These applications seem to firmly fall into the "I'm willing to compromise on quality if I don't have to pay a living person a wage" niche, so they're value-destroying, not value-creating.
Are there examples of value-creating applications for ML? (From a business point of view; obviously the "shitty translations but at no cost" proposition creates value for the average Internet user.)
In either case it is only 'value-destroying' if the business has unlimited resources.
I'm talking about commercial applications, like the OP said. That is, things I could potentially pitch to management and substantiate with something concrete that isn't "you can fire your lowest-paid contractors now".
At any rate here are way more than 3 other uses of DL today off the top of my head:
* Autocompletion (be it in search engines toolbars or in Gmail/Word/...)
* Superresolution GAN, the most interesting example to me being NVIDIA DLSS, you render a game at ~720p or less and then upscale it to the target resolution of 1080p or 4k, allowing to get quality that the machine would not have been able to support at the target resolution directly.
* Image recognition/tagging: Most of this is used in the security domain, but there is also a lot of stuff around inventory management, safety etc.
* Semantic search
* Protein folding (AlphaFold)
* In astrophysics: detection of supernovaes, FRBs and probably a bunch of other stuff I'm not aware of
* Self-driving cars: Even assuming self-driving technology does not evolve anymore from now on, the current state of the art is still a selling point.
* Predictive maintenance: Used for plane engines and other things