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Thanks for the link. But truly I spend the majority of my time reading the science and math. I prefer to arrive at my own conclusions and then compare those conclusions to whatever is in currency.

For instance, on the complexity issue I found myself sharing some observations with Jewish Physicist Gerald Schroeder and not enthused by the "irreducibly complex" argument - mostly because it is backwards looking and therefore baits the same types of counter-arguments that evolution theory baits: absence of evidence is evidence of absence or not. Too much toggling between positions, too much heat, not enough light.

So I am drawn to the forward looking models, e.g. the AP Model, self-organizing complexity, cellular automata.

Thanks for the link. But truly I spend the majority of my time reading the science and math. I prefer to arrive at my own conclusions and then compare those conclusions to whatever is in currency.

Then you are no doubt drawn to the most current work, which includes the work of Szostak.

I’m going to return to the recent (so recent it hasn’t actually been published yet) paper by Dembski and Marks. In it he rather explicitly states that an evolutionary algorithm accumulates active information from the environmental response to change. This can be observed in living things via experimentation, and it can be simulated with computer algorithms.

So there are a couple of remaining questions. Dembski’s question is whether evolutionary algorithms are efficient enough to account for the speed of biological evolution. (Also Behe’s question.)

Your question appears to be how did the algorithm originate, or how did the algorithm become embodied in living things.

That is why Szostak’s work is so important, because he is investigating whether chemistry can evolve an instance of a structure that can continue evolving.