Options and Fine-Tuning

OPTIONS and FINE-TUNING:

You will achieve the best results if you can select the most ideal option from any set of options.  However, it is much better to be able to choose the best out of a set of, say, 100 options than to only be able to choose the best out of a set of 10 options.  In general, when you have a greater number of options to choose from, and can choose the most ideal option from this set, you will get better results than if you only had a smaller set of options to choose from.

In addition, each option may be expanded into a set of sub-options.  These sub-options may continue expanding to further layers of depth into sub-sub-options, sub-sub-sub-options and so on.  The most powerful systems to work with are those that have a manageable set of options at each layer, but can be expanded to multiple layers of depth.  With this, the options can always be refined for more customization.  This is called fine-tuning.

With fine-tuning systems, you will be able to select the best option from an exponentially large set of options.  Suppose that each layer has 100 options and you can explore a depth of 5 layers.  This gives a total of 100^5 = 10 billion options.  But one need not search through 10 billion possibilities to find the most ideal option.  You only need to search through 100 options at each of the 5 layers.  This means that fine-tuning systems have logarithmic search time.

Again, more options means better results, but exponentially many more options means exponentially better results.  If you can select the best option from a set of 10 billion options, you will have exponentially better results than only being able to choose from a set of 100 options.