168 karma · joined June 21, 2019
As I understand it, one of the big advantages of T9 had over other, more sophisticated forms of predictive text is that each word in the dictionary can be encoded in close to 1 byte. Given the constraints faced at the time, T9 feels to me like it is close to a local optimimum.
For this task, I was primarily interested in whether the task would work at all. My assumption is that given we can optimise for these texts, we could optimise for more representative datasets, too. Perhaps you think this is a weak assumption?
Do you think testing on a sample of totally different texts from different authors would be more convincing?
https://github.com/Torvaney/flow-solver
Although I used a much lazier strategy for doing the solving (reduction to SAT).