On Thu, Sep 5, 2013 at 8:17 AM, Carl Gundel <ca...@psychesystems.com> wrote:
> I’m not sure why you think I’m attributing special reverence to > computing. Break all the rules, please. ;-) > To say you're "touching the hem" generally implies you're also on your knees and bowing your head. > **** > > ** ** > > The claim that life is somehow inefficient so that computing should be > different begs for qualification. I’m sure there are a lot of ideas that > can be gleaned for future computing technologies by studying biology, but > living things are not computers in the sense of what people mean when they > use the term computer. It’s apples and oranges. > I agree we can gain some inspirations from life. Genetic programming, neural networks, the development of robust systems in terms of reactive cycles, focus on adaptive rather than abstractive computation. But it's easy to forget that life had millions or billions of years to get where it's at, and that it has burned through materials, that it fails to recognize the awesomeness of many of the really cool 'programs' it has created (like Wolfgang Amadeus Mozart ;). A lot of logic must be encoded in the heuristic to evaluate some programs as better than others. It can be difficult to recognize value that one did not anticipate finding. It can be difficult to recognize how a particular mutation might evolve into something great, especially if it causes problems in the short term. The search space is unbelievably large, and it can take a long time to examine it. It isn't a matter of life being 'inefficient'. It's that, if we want to use this 'genetic programming' technique that life used to create cool things like Mozart, we need to be vastly more efficient than life at searching the spaces, developing value, recognizing how small things might contribute to a greater whole and thus should be preserved. In practice, this will often require very special-purpose applications - e.g. "genetic programming for the procedural generation of cities in a video game" might use a completely different set of primitives than "genetic programming for the facial structures and preferred behaviors/habits of NPCs" (and it still wouldn't be easy to decide whether a particular habit contributes value). Machine code - by which I mean x86 code and similar - would be a terribly inefficient way to obtain value using genetic programming. It is far too fragile (breaks easily under minor mutations), too fine grained (resulting in a much bigger search space), and far too difficult to evaluate. Though, we could potentially create a virtual-machine code suitable for genetic programming.
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