23-03-2026, 09:25 PM
(23-03-2026, 05:30 PM)eggyk wrote: You are not allowed to view links. Register or Login to view.So as long as we're talking in our own words, how does your theory explain the statistical properties of the text? I don't understand how it does that.
Even though, as I've already explained, that's not really the main point, I'll try to go into a bit more detail without giving a lecture that’s too long—which, admittedly, isn't exactly my strong suit (I hope I can still slip in some of my "AI like humor"
)Imagine a circle with five wheels - these are needed to represent most of the VMS words (surprisingly, no more than that). Each circle contains a selection of specific prefixes, suffixes, and middle parts—five in total.
The interesting thing is that these parts are likely allusions to Llull’s elements. The letters as abbreviations for divine attributes: B for Bonitas, C for Magnitudo, and so on. So it cannot be ruled out that something similar is going on here. "o" "qo" "qot" "ody" etc.—these could be abbreviations for spiritual qualities or relationships, following the same Llullian logic. I cannot prove this. But it would fit. That does not mean, however, that a normal text is generated, but only that one is playing around with properties in the Llullian tradition.
You spin. Most combinations occur rarely - a few appear constantly. That is exactly the Zipf distribution. As mentioned earlier, Mandelbrot proved this. It follows from the mathematics. But there must be other rules or mechanisms at work that form these patterns. The Naibbe cipher has at least pointed us in the right direction.
Low entropy follows the same logic in principle. The fields are not independent - not every combination is valid. These constraints reduce entropy. And as it turns out, significantly - exactly what we observe.
But what about the long-range correlations? That is the “Stuck-Wheel” effect I described above. When the mechanism lingers for a page or two on a core element—chol, cheody, or the like—local patterns persist across many lines.
The problem remains: if you want to generate exactly a VMS text, you have to know exactly what a VMS text is; we do have statistics, but the statistics are limited to a single manuscript, and what we don’t know is how much everything would change if we were to alter only small parts of the encoding system. Currier A / B already demonstrate this impressively...

