There are several problems with the paper and with the idea itself. First, code is unavailable - github repository [1] does not contain any code. [1] https://

There are several problems with the paper and with the idea itself. First, code is unavailable - github repository [1] does not contain any code. [1] https://github.com/tgchomia/ts https://github.com/tgchomia/ts The algorithm, itself, has some black holes. For example, 256 integer codes are turned into 6 groups at some point. How? Why six groups? Algorithm, also, does not create a model per se, it needs a history of previous observations to compute predictions from. What is interesting there is that contexts are compared on the curvatures in them, not on actual values. This generalizes to many applications, including language modeling, I think.