I used games as examples just because they are the easiest to understand and most popular applications of RL, and also very general, but that would be like saying that CNNs are useless because recognizing cats is not a bussiness, recognizing cats is just 1 example of the vast array of things CNNs can do. For every optimization algorithm pioneered by RL research in order to play a useless $0-return game, you can bet that it's later implemented and used in other areas to save and generate millions or billions of dollars. Games are just the test playground for new research.
I don't understand how #3 can't be credited with the billions of dollars the products and services based on it generate. According to [2], the global market of offering a speech-to-text API is valued at 1.3 billion dollars in 2019, if you assume that just 20% of that is actual customer value (to account for hype, errors in valuation, etc...), that's about 260 million dollar per year. Even an extremly conservative value estimate tells you the technology generates a billion dollar every 4 year (if it stays constant, the forecast projects the market will reach >3 billions by 2027). Keep in mind that this does not include any value generated from any other component or product, this is just the profits from the APIs alone, the generous 20% discount is to account for hype, analysis errors and bad data.
But you know what ? the broader point is, these are just 3 examples that I pulled off the top of my head while I was making a 5 minute comment without consulting google. And considering the person I'm replying to never provided a single example or any kind of specific clarification till now, or anwered any of my questions or otherwise offered any kind of rebuttal, I think it's pretty fair to say they hold up nicely.
[0] https://developer.nvidia.com/blog/designing-arithmetic-circu...
[1] https://www.nature.com/articles/s41586-021-04301-9
[2] https://www.fortunebusinessinsights.com/speech-to-text-api-m...