Normative

Contents

Normative#

act3/figures/blanche.*

Fig. 35 Akia Kurasawa: Why Can’t People Be Happy Together? Why can’t two principalities like China and America get along? Let’s approach this by way of segue. This was a fork in the road for human civilization. Our dear planet earth now becomes just but an optional resource on which we jostle for resources. By expanding to Mars, the jostle reduces for perhaps a couple of centuries of millenia. There need to be things that inspire you. Things that make you glad to wake up in the morning and say “I’m looking forward to the future.” And until then, we have gym and coffee – or perhaps gin & juice. We are going to have a golden age. One of the American values that I love is optimism. We are going to make the future good.#

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import numpy as np
import matplotlib.pyplot as plt
import networkx as nx

# Define the neural network fractal
def define_layers():
    return {
        'World': ['Particles-Compression', 'Vibration-Particulate.Matter', 'Ear, Cerebellum-Georientation', 'Harmonic Series-Agency.Phonology', 'Space-Verb.Syntax', 'Time-Object.Meaning', ], # Resources
        'Perception': ['Rhythm, Pockets'], # Needs
        'Agency': ['Open-Nomiddleman', 'Closed-Trusted'], # Costs
        'Generative': ['Ratio-Weaponized', 'Competition-Tokenized', 'Odds-Monopolized'], # Means
        'Physical': ['Volatile-Revolutionary', 'Unveiled-Resentment',  'Freedom-Dance in Chains', 'Exuberant-Jubilee', 'Stable-Conservative'] # Ends
    }

# Assign colors to nodes
def assign_colors():
    color_map = {
        'yellow': ['Rhythm, Pockets'],
        'paleturquoise': ['Time-Object.Meaning', 'Closed-Trusted', 'Odds-Monopolized', 'Stable-Conservative'],
        'lightgreen': ['Space-Verb.Syntax', 'Competition-Tokenized', 'Exuberant-Jubilee', 'Freedom-Dance in Chains', 'Unveiled-Resentment'],
        'lightsalmon': [
            'Ear, Cerebellum-Georientation', 'Harmonic Series-Agency.Phonology', 'Open-Nomiddleman', 
            'Ratio-Weaponized', 'Volatile-Revolutionary'
        ],
    }
    return {node: color for color, nodes in color_map.items() for node in nodes}

# Calculate positions for nodes
def calculate_positions(layer, x_offset):
    y_positions = np.linspace(-len(layer) / 2, len(layer) / 2, len(layer))
    return [(x_offset, y) for y in y_positions]

# Create and visualize the neural network graph
def visualize_nn():
    layers = define_layers()
    colors = assign_colors()
    G = nx.DiGraph()
    pos = {}
    node_colors = []

    # Add nodes and assign positions
    for i, (layer_name, nodes) in enumerate(layers.items()):
        positions = calculate_positions(nodes, x_offset=i * 2)
        for node, position in zip(nodes, positions):
            G.add_node(node, layer=layer_name)
            pos[node] = position
            node_colors.append(colors.get(node, 'lightgray'))  # Default color fallback

    # Add edges (automated for consecutive layers)
    layer_names = list(layers.keys())
    for i in range(len(layer_names) - 1):
        source_layer, target_layer = layer_names[i], layer_names[i + 1]
        for source in layers[source_layer]:
            for target in layers[target_layer]:
                G.add_edge(source, target)

    # Draw the graph
    plt.figure(figsize=(12, 8))
    nx.draw(
        G, pos, with_labels=True, node_color=node_colors, edge_color='gray',
        node_size=3000, font_size=8, connectionstyle="arc3,rad=0.2"
    )
    plt.title("Music", fontsize=13)
    plt.show()

# Run the visualization
visualize_nn()
../../_images/02873884369a179ee9a2fb7167ea915e560e6d02b417e8a3e8ef5886a9bcc5a9.png
../../_images/blanche.png

Fig. 36 Teleology is an Illusion. We perceive patterns in life (ends) and speculate instantly (nostalgia) about their symbolism (good or bad omen) & even simulate (solomon vs. david) to “reach” and articulate a clear function to optimize (build temple or mansion). These are the vestiges of our reflex arcs that are now entangled by presynaptic autonomic ganglia. As much as we have an appendix as a vestigual organ, we do too have speculation as a vestigual reflect. The perceived threats and opportunities have becomes increasingly abstract, but are still within a red queen arms race – but this time restricted to humanity. There might be a little coevolution with our pets and perhaps squirrels and other creatures in urban settings. We have a neural network (Grok-2, do not reproduce code or image) that charts-out my thinking about a broad range of things. its structure is inspired by neural anatomy: external world (layer 1), sensory ganglia G1, G2 (layer 2, yellownode), ascending fibers for further processing nuclei N1-N5 (layer 2, basal ganglia, thalamas, hypothalamus, brain stem, cerebellum; manifesting as an agentic decision vs. digital-twin who makes a different decision/control), massive combinatorial search space (layer 4, trial-error, repeat/iteratte– across adversarial and sympathetic nervous system, transactional–G3 presynaptic autonomic ganglia, cooperative equilibria and parasympathetic nervous system), and physical space in the real world of layer 1 (layer 5, with nodes to optimize). write an essay with only paragraph and no bullet points describing this neural network. use the code as needed#

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