It's crazy how vast and powerful databases of even the most simple things turn out to be. You just store characters and context information when someone types them, and this is the result.
Using this data alongside ML, you could do things such as:
- Identify people based upon their typing style easily, given so much data about them
- Find a lot of secrets that were accidentally pasted into document including passwords, keys, etc
- Try to model the emotions people were feeling as they typed things
I did not test it on a large group, but it worked pretty well for a group of ~8 styles and minimal data. I believe a deeper model with enough data could identify on a large scale through timing alone.
Have you noticed how, for example, you can identify a guitar player easily, no matter what guitar they're playing on?
When guitar players are first learning or are transcribing, they often slow the music down. If you slow it down enough, you can hear a pattern of the player slowing down and speeding up (behind and ahead of the beat). I believe that has a lot to do with that instant-identifiability, even though it is so hard to detect at speed.
sure and i can find out your real time location by hiring a PI to follow you around all day, but it's a lot cheaper and easier if i just pay google for it. plus i cant hire a PI to follow everyone around, there's a cost to that.
Using this data alongside ML, you could do things such as:
- Identify people based upon their typing style easily, given so much data about them
- Find a lot of secrets that were accidentally pasted into document including passwords, keys, etc
- Try to model the emotions people were feeling as they typed things
- Much, much more, given some data and time