> In the video, the user is typing 'Thumbs up', and when they get to the first 'u' the keyboard shows a 'u' being pressed but a 'j' is inserted instead. Are you suggesting that, due to the way most people construct sentences, the OS thinks that 'thjmbs' is the most likely word? And then the next time the OS thinks that 'thhmbs' is the most likely word?

In addition to the other problems (the keyboard being too prone catching extremely subtle slides below UI response time), there certainly is the problem of when you crowd source enough data you crowd source all of their collective mistakes, too. In a lot of that raw data mistakes are going to be as common or more common than corrections and/or originally correct spellings.

We do have a great filter for this called a "dictionary", but as the above commenter laments companies have given up on "just autocorrect to dictionary words" for much more complex "learning" models and filtering them back to just dictionary words is antithetical to the (sunken cost) expense that went into training these models, and/or the KPIs and promotion incentives that keep prioritizing "AI" and giant crowd sourced data vats over simpler mechanics and local user specifics.

No dude it's just a bug. Watch the video.