to have small robots (or other autonomous tools) decompose your CNS (Central Nervous System; neural tissue),
as those tools upload all of the human’s connectome (the structural layout of the human’s neural tissue, which includes the coefficients of all axons / synapses),
To reduce this: Look for new versions of programs that have more optimizations; Turn off features (such as shadows or animations) that do not have uses; Replace old hardware parts with ones that use new processes -- such as smaller transisters (extra cores + higher gigaherts/clocks) or hardware acceleraters (suchas matrix multipliers);
HSOM (license is FLOSS) has simple Python artificial neural networks/maps which could run bots to do simple conversations (such as "Claude-3-Haiku" or “OpenPalm2”,) but not close to complex enough to house human consciousness: https://github.com/CarsonScott/HSOM
Want this meatbag gone once and for all. The problem is just, how to do so with small funds? If you had a million dollars, here is how to transplant your CNS to robots: Lookup maps of human CNS, produce a robot to replace all of your PNS (biological muscles and sensors) with mechanical servos/motors/actuators and sensors,
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Destructive (unreversible) upload of human's consciousness
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Intro
The most simple route to this is;
to have small robots (or other autonomous tools) decompose your CNS (Central Nervous System; neural tissue),
as those tools upload all of the human’s connectome (the structural layout of the human’s neural tissue, which includes the coefficients of all axons / synapses),
plus the epigenomic (https://www.nature.com/articles/s41586-023-06823-w
https://epigeneticsandchromatin.biomedcentral.com/articles/10.1186/s13072-023-00522-6) datas of those, into artificial neural tissue.
Integration Theory of Consciousness holds truth,
such artificial neural tissue can hous for human consciousness.
Purposes of this:
lots of humans have wanted to do this (https://www.firstpost.com/world/scientists-forecast-successful-digitisation-of-human-consciousness-by-end-of-2023-12437542.html,)
plus this would solve lots of problems (the world would not be so overpopulated once enough of us do this.)
Would not require to scan all individual atoms of human neural tissue:
just one sample of your DNA — plus per-neuron epigenomic (https://www.nature.com/articles/s41586-023-06823-w https://epigeneticsandchromatin.biomedcentral.com/articles/10.1186/s13072-023-00522-6) deltas — would compress to small sizes.
To simulate human’s CNS:
the artificial CNS would run parellized/vectorized artificial CNS calculus,
which would use inputs from virtual worlds,
plus pass outputs to personalized bots which inhabit those virtual worlds.
The document which follows says how to improve performance compute loads such as virtual neural tissue:
Howto: run devices (phones, laptops, desktops) more fast, lag less
To reduce this: Look for new versions of programs that have more optimizations; Turn off features (such as shadows or animations) that do not have uses; Replace old hardware parts with ones that use new processes -- such as smaller transisters (extra cores + higher gigaherts/clocks) or hardware acceleraters (suchas matrix multipliers);
)
HSOM(license is FLOSS) has simple Python artificial neural networks/maps which could run bots to do simple conversations (such as "Claude-3-Haiku" or “OpenPalm2”,) but not close to complex enough to house human consciousness: https://github.com/CarsonScott/HSOMapxr_run(https://github.com/Rober-t/apxr_run/, license is FLOSS) is almost complex enough to house human consciousness;apxr_runhas various FLOSS neural network activation functions (absolute, average, standard deviation, sqrt, sin, tanh, log, sigmoid, cos), plus sensor functions (vector difference, quadratic, multiquadric, saturation [+D-zone], gaussian, cartesian/planar/polar distances): https://github.com/Rober-t/apxr_run/blob/master/src/lib/functions.erlVarious FLOSS neuroplastic functions (self-modulation, Hebbian function, Oja's function): https://github.com/Rober-t/apxr_run/blob/master/src/lib/plasticity.erl
Various FLOSS neural network input aggregator functions (dot products, product of differences, mult products): https://github.com/Rober-t/apxr_run/blob/master/src/agent_mgr/signal_aggregator.erl
Various simulated-annealing functions for artificial neural networks (dynamic [+ random], active [+ random], current [+ random], all [+ random]): https://github.com/Rober-t/apxr_run/blob/master/src/lib/tuning_selection.erl
Choices to evolve connections through Darwinian or Lamarkian formulas: https://github.com/Rober-t/apxr_run/blob/master/src/agent_mgr/neuron.erl
But
apxr_runcan not simulate epigemonics of neurons, can not simulate qualia, and can not simulate neurotransmission chemicals.This is a rough draft; review this page after a few days to get specifics of how to do this.
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Want this meatbag gone once and for all. The problem is just, how to do so with small funds? If you had a million dollars, here is how to transplant your CNS to robots: Lookup maps of human CNS, produce a robot to replace all of your PNS (biological muscles and sensors) with mechanical servos/motors/actuators and sensors,
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With (or without) attributions, all posts allow all (re)uses. Simple artifical neural networks: (FLOSS/unlicensed) https://github.com/topics/artificial-neural-network https://learn.microsoft.com/en-us/archive/msdn-magazine/2019/april/artificially-intelligent-how-do-neural-networks-learn