| > And the genius of the Turing Machine (and equivalent) is that at the foundation of things, you do not need a lot of symbols and a lot of rules. I think at the core of our arguments lies this. Turing representation, i.e., the Turing Machine is the fundamental computing engine that can represent any problem and provide a solution to that problem, in whatever n-space dimension the problem finds itself in. It is the binary representation of any problem space. Yet no one uses it to do the real world problem solving. Why? Because its symbolism is to verbose for even the simplest solution. Herein lies what I have come to realise: its verbosity that a 2D representation can reduce at the expensive of flexibility. As the textual representation is a trade-off, so is the visual one. Text happens to be extremely flexible for problem representation and solution but it is less verbose than a Turing Machine and based on the self principles, so we can be assured of its universality. Yet textual representation can still become very verbose and hard to understand (hence version control and diff'ing tools). A 2D solution can be even less verbose at the price of flexibility - a 2D representation is more bound to the problem space being addressed. I think the win comes when a recognition arises that points to a visual representation as being less verbose and therefore more understandable because the problem space is confined and well understood that there is no longer a need for texts flexibility. This being akin to a DSL definition for the problem space. |