{Chaotic Determinism (+ Extracts) [continued (14)]}[4th August 1988]

[Redbook5:255-256][19880804:1705]{Chaotic Determinism (+ Extracts) [continued (14)]}[4th August 1988]

.1705

‘A drop filling with water is like a little elastic bag of surface tension, oscillating this way and that, gaining mass and stretching its walls until it passes a critical point and snaps off. A physicist trying to model the drip problem completely – writing down sets of coupled non-linear partial differential equations with appropriate boundary conditions, and then trying to solve them – would find himself lost in a deep, deep thicket.

*

‘An alternative approach would be to forget about the physics and look only at the data,** as though it were coming out of a black box. Given a list of numbers representing intervals between drips, could an expert in chaotic dynamics find something useful to say? Indeed, as it turned out, methods could be devised for organising such data and working backwards into the physics,*** and these methods became critical to the applicability of chaos to real-world problems.’****

‘The choice is always the same. You can make your model more complex and more faithful to reality, or you can make it simpler and easier to handle.’#

*Ibid [Gleick, ‘Chaos, Making a New Science’, Heinemann, London, 1988], p263

**[Which is broadly how most so-called Artificial Intelligence applications currently (2018) work?]

***[Which – working back from data into the physics – is probably not how most Artificial Intelligence applications currently (2018) work....]

****Ibid, p263-4

#Ibid, 278

[continues]

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