> On 31 Mar 2018, at 23:12, Mindey I. <min...@mindey.com> wrote:
> 
> Why not to just define yourself, and then try to re-run yourself? If you have 
> a mathematical definition of your own self, you are already close to living 
> forever as a running process based on that definition.

You cannot. It is a theorem in arithmetic: no universal machine can define 
itself. You can bet on a level of substitution, but you can’t prove, not even 
experimentally to yourself that you have found it. All this is detailed in some 
of my papers, or my older long texts.

Note that all computations are executed (in the original mathematical sense of 
Post, Church, Turing, …) in arithmetic. If you believe that a proposition like 
3^3 + 4^3 + 5^3 is equal to 6^3 independently of you verifying that fact or 
not, you are already “there”.

> 
> Personally, when I try to define myself, I bump into memories of strong sense 
> of curiosity, making me nearly cry of desire to know Everything.
> 
> Maybe most of us here on the "Everything-List" are like that. Maybe we're 
> equivalent?


Yes, that is the natural mystical understanding of the average universal 
numbers: there is only one person, but locally disconnected. I sum up often by 
“we are god playing hide-and-seek with Itself”, but the details of this are 
more demanding in machine’s theology (probability logic).

Bruno




> 
> On 31 March 2018 at 20:32, Telmo Menezes <te...@telmomenezes.com 
> <mailto:te...@telmomenezes.com>> wrote:
> On Sat, Mar 31, 2018 at 10:17 PM, Lawrence Crowell
> <goldenfieldquaterni...@gmail.com <mailto:goldenfieldquaterni...@gmail.com>> 
> wrote:
> > You would have to replicate then not only the dynamics of neurons, but every
> > biomolecule in the neurons, and don't forget about the oligoastrocytes and
> > other glial cells. Many enzymes for instance to multi-state systems, say in
> > a simple case where a single amino acid residue of phosphorylated or
> > unphosphorylated, and in effect are binary switching units. To then make
> > this work you now need to have the brain states mapped out down to the
> > molecular level, and further to have their combinatorial relationships
> > mapped. Biomolecules also behave in water, so you have to model all the
> > water molecules. Given the brain has around 10^{25} or a few moles of
> > molecules the number of possible combinations might be on the order of
> > 10^{10^{25}} this is a daunting task. Also your computer has to accurately
> > encode the dynamics of molecules -- down to the quantum mechanics of their
> > bonds.
> >
> > This is another way of saying that biological systems, even that of a basic
> > prokaryote, are beyond our current abilities to simulate. You can't just
> > hand wave away the enormous problems with just simulating a bacillus, let
> > alone something like the brain. Now of course one can do some simulations to
> > learn about the brain in a model system, but this is far from mapping a
> > brain and its conscious state into a computer.
> 
> Well maybe, but this is just you guessing.
> Nobody knows the necessary level of detail.
> 
> Telmo.
> 
> > LC
> >
> >
> > On Saturday, March 31, 2018 at 10:31:56 AM UTC-6, John Clark wrote:
> >>
> >> On Tue, Mar 27, 2018 at 8:24 PM, Lawrence Crowell
> >> <goldenfieldquaterni...@gmail.com 
> >> <mailto:goldenfieldquaterni...@gmail.com>> wrote:
> >>
> >>> > Yes, and if you replace the entire brain with technology the peg leg is
> >>> > expanded into an entire Pinocchio. Would the really be conscious? It is 
> >>> > the
> >>> > case as well that so much of our mental processing does involve hormone
> >>> > reception and a range of other data inputs from other receptors and 
> >>> > ligands.
> >>
> >> I see nothing sacred in hormones, I don't see the slightest reason why
> >> they or any neurotransmitter would be especially difficult to simulate
> >> through computation, because chemical messengers are not a sign of
> >> sophisticated design on nature's part, rather it's an example of 
> >> Evolution's
> >> bungling. If you need to inhibit a nearby neuron there are better ways of
> >> sending that signal then launching a GABA molecule like a message in a
> >> bottle thrown into the sea and waiting ages for it to diffuse to its random
> >> target.
> >>
> >> I'm not interested in chemicals only the information they contain, I want
> >> the information to get transmitted from cell to cell by the best method and
> >> so I would not send smoke signals if I had a fiber optic cable. The
> >> information content in each molecular message must be tiny, just a few bits
> >> because only about 60 neurotransmitters such as acetylcholine,
> >> norepinephrine and GABA are known, even if the true number is 100 times
> >> greater (or a million times for that matter) the information content ofeach
> >> signal must be tiny. Also, for the long range stuff, exactly which neuron
> >> receives the signal can not be specified because it relies on a random
> >> process, diffusion. The fact that it's slow as molasses in February does 
> >> not
> >> add to its charm.
> >>
> >> If your job is delivering packages and all the packages are very small and
> >> your boss doesn't care who you give them to as long as it's on the correct
> >> continent and you have until the next ice age to get the work done, then 
> >> you
> >> don't have a very difficult profession. I see no reason why simulating that
> >> anachronism  would present the slightest difficulty. Artificial neurons
> >> could be made to release neurotransmitters as inefficiently as natural ones
> >> if anybody really wanted to, but it would be pointless when there are much
> >> faster ways.
> >>
> >> Electronics is inherently fast because its electrical signals are sent by
> >> fast light electrons. The brain also uses some electrical signals, but it
> >> doesn't use electrons, it uses ions to send signals, the most important are
> >> chlorine and potassium. A chlorine ion is 65 thousand times as heavy as an
> >> electron, a potassium ion is even heavier, if you want to talk about gap
> >> junctions, the ions they use are millions of times more massive than
> >> electrons. There is no way to get around it, according to the fundamental
> >> laws of physics, something that has a large mass will be slow, very, very,
> >> slow.
> >>
> >> The great strength biology has over present day electronics is in the
> >> ability of one neuron to make thousands of connections of various strengths
> >> with other neurons. However, I see absolutely nothing in the fundamental
> >> laws of physics that prevents nano machines from doing the same thing, or
> >> better and MUCH faster.
> >>
> >>   John K Clark
> >>
> >>>
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> -- 
> Mindey I.
> 0x5F5CC7AD
> https://mindey.com <https://mindey.com/>
> Scientific Computing
> & Web Applications
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