I'm totally frazzled from a month of two sick kids and tax filing — and yes, I wrote this before I started at SFI and have since had plenty of opportunity to refine my thinking on these matters — but no, I meant entropic: a highly ordered universe is considerably LESS likely (at least in the terms I understand all of this, so I'm treading lightly as I'm not as numerate with the formalisms as you seem to be from other correspondence we've had elsewhere). But perhaps we're talking about the same thing, as what I'm suggesting here is that an all-options multiverse is the outcome of the most parsimonious algorithm, rather than conditions that favor one outcome to the exclusion of others.
Any individual universe in such a multiverse may APPEAR mysteriously ordered, but it's an artifact of sampling bias. Any infinite bit string is going to, like the proverbial monkeys on typewriters, eventually going to generate something that seems exquisitely ordered, but we don't need to invoke a convoluted explanation for this the way that, for instance, creationists insist we need Intelligent Design to explain abiogenesis (or else we have "a tornade blowing through a junkyard and assembling a working 747").
Maybe a deeper point I'm trying to make in this book is that order and noise are ultimately epistemic properties, not ontological properties. Murray Gell-Mann and Miguel Fuentes have both written about this from a formal math perspective, and I talk about it some with Miguel in his episode of Complexity Podcast. I argue this from a different angle in my Return.Life essay, "The Future is Noisy," which will likely go toward to the end of this albatross of an unfinished book...and Tyson Yunkaporta talks about how matters of entropy are ultimately artifacts of closed systems, and would you kindly show him a truly closed system, in his book Sand Talk.
I'm happy to talk about this more with you when we can find the time, and eager to learn more and perhaps have you show me the error of my ways...
Thanks for reading this so closely!
<3
