If you have a closure over the whole universe and you are given one knob to turn, and once doing so out pops a new projection of the world you can see, then you 1) don't necessarily see the whole universe, but 2) can potentially be a specialist in the things that are observable in that projection. The part I don’t like in this picture is that the niche-fillers start to fancy the idea there are different universes popping out the closure and see no need to reconcile them. They see N vectors instead of one eigenvector.
-----Original Message----- From: Friam [mailto:friam-boun...@redfish.com] On Behalf Of glen Sent: Monday, May 09, 2016 5:00 PM To: friam@redfish.com Subject: Re: [FRIAM] Tagged "Get off my lawn!" You're dancing around the fundamental point: Can abstraction layers be closures? And that's the essence of complexity theory, the study of what and how some thing is reducible to the inner layers (or what and how expands to the outer layers). Can you really understand Go just by knowing the rules? Or can you understand it without knowing the rules, just knowing possible configurations? The bias in Western culture seems to lie in the forward map. We tend to have a deep desire to build everything from 1st principles, axioms. (And even when we're fundamentally ignorant, we pretend at understanding the principles.) It's not enough to be an artisan. You have to be a scientist. So, your qualifier, without regard to coherence or extension, is over-simplification. What's actually happening is specialization, niche-filling ... the same thing that's been happening the whole time. And it is definitely _not_ without regard. It may be systemic or evolutionary (so that no single mind understands what's happening). But to assert that there is no order or pattern to specialization seems wrong (at least too strong). On 05/09/2016 03:37 PM, Marcus Daniels wrote: > One can learn to program in, say, Python without understanding a given > machine instruction set. One can even learn a subset, and have a correct > understanding of some of its syntax and semantics and little or no > understanding of other parts. That doesn't mean that learning the rest is > pointless, or that learning a machine language couldn't give a Python > programmer deeper and useful insight into why some constructs are slow and > others are fast. Or that learning about digital circuit design couldn't > give insight into what makes a machine instruction set energy efficient. Or > that learning quantum mechanics couldn't give some insight into what makes > circuits work the way they do. All these tools can be useful and the > connections between them are some of the most interesting and useful things > to know. This trend toward "industry relevant" knowledge is just to say the > graph should be chopped up into consumable sound bites without regard to > their coherence or utility for learnin g other things. -- ⛧ glen ============================================================ FRIAM Applied Complexity Group listserv Meets Fridays 9a-11:30 at cafe at St. John's College to unsubscribe http://redfish.com/mailman/listinfo/friam_redfish.com ============================================================ FRIAM Applied Complexity Group listserv Meets Fridays 9a-11:30 at cafe at St. John's College to unsubscribe http://redfish.com/mailman/listinfo/friam_redfish.com
