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[Max White]

So your going to apply the principle of evolution to the principle of evolution?

That would imply that one test was 'better' then another in a way, so more effective (Measured in how precise and accurate it is) , and efficiently (How fast it preforms these operations). However, most generic algorithms work by returning a boolean, that is "Is A better then B", so assuming were getting a boolean back, there is no way to make it more effective, just more efficient. Now your making algorithms that may or may not be accurate, so you need a solution to compare to, but then then you can't be 100% sure it will always return the correct answer. The only way is to prove it is mathematically the same as your first generic algorithm, and then you might as well have just derived the best algorithm from the original in the first place. So it is sort of pointless...

[Siquo]

It was just a dream, there was no hidden insight, it was just a flight of fancy. That isn't a bad thing, you can still use the inspiration to do great (possible) things.

For every success there's millions of failures.

But I think he's just trying to establish how often mutations or cross-linking happens, how many sexual partners should be included into an offspring (who said two is the best number? *nudgenudge winkwink*) and so forth, creates an optimal way of generating solutions. That's a lot easier than "arbitrary algorithm". It's kind of meta, but in real life it's also in our code: How often mutations happen, cross linking and our number of parents is also encoded in the same genes.