The cloths brand position themselves as vertically integrated manufacturer - they manufacture their own yarn, knit the cloth, cut the fabric, sew the garments and package the products themselves.
I do not know enough of this business to understand whether they apply made-to-measure approaches - defining products that are made from a standard-sized base pattern but customized for individual requirements. However.
The Bottom-Up approach of Artificial Intelligence.
Intelligent behavior is reconstructed starting with the most simple functions/programs, interweaved in superior layers causing the emergence of complex structures.
This is in contrast to the approaches derived from the symbol system hypothesis that intelligence operate on a system of symbols by reasoning or inference engines.
Mathematical Problem Solving.
Symbolic computation is promising closed form solutions (of good nature for exact results), but the "worlds" its models describe are often too small. Numerical approaches look much more bottom-up by decomposition of domains and special mathematical functions into simple mathematical behavior. It usually covers much more problem domains and classes.
Ironically, in an inverse problem view you look for models that predict behavior you have observed or want to control. Symbols will help you to understand, calibrate, ..
I have mentioned that we face such problem in advanced quantitative finance - UnRisk. Mathematica is indispensable for our ambitious approaches. Not only that it covers all of the above paradigms in a uniform way and high-level language representation, its unprecedented software development support, significantly enhanced in Mathematica 8, allows UnRisk to do things that cannot be done without. And, when we take UnRisk/Mathematica to quant finance professionals in financial institutions they do things the Mathematica way, which Mathematica could not do ....
I call this co-evolution.
