15-09-2020, 05:58 AM
Perhaps yet another short summary:
Torsten's input is something that is like a correlation: similar words tend to appear near each other.
This correlation is converted into a causality: this happens because the writer took previous words, modified them a bit and wrote them down again.
One cannot go from correlation to causality without extra data/information.
The only extra data/information presented is the output of Torsten's App. We don't know what it does exactly.
On top of that, it has been demonstrated that a simple method of converting a meaningful text to unreadable text can have exactly the same property as seen in the MS. This shows that the conclusion that the text is meaningless is not a valid conclusion.
Torsten's input is something that is like a correlation: similar words tend to appear near each other.
This correlation is converted into a causality: this happens because the writer took previous words, modified them a bit and wrote them down again.
One cannot go from correlation to causality without extra data/information.
The only extra data/information presented is the output of Torsten's App. We don't know what it does exactly.
On top of that, it has been demonstrated that a simple method of converting a meaningful text to unreadable text can have exactly the same property as seen in the MS. This shows that the conclusion that the text is meaningless is not a valid conclusion.