Catalysts

The struggle between centralized banking cartels and decentralized blockchain systems mirrors the broader dichotomy between entrenched power structures and emerging public infrastructures. At its core, the banking cartel operates as a tightly controlled network of private ledgers. These ledgers are the lifeblood of financial transactions, ensuring that payments are balanced, customers are satisfied, and the system remains insulated from public scrutiny. This network thrives on exclusivity, where trust is established not through transparency but through a long history of institutional dominance. Customers in this framework are beneficiaries but also captives—liberated only within the confines of what the cartel deems appropriate.

The usurper of this order is the public infrastructure represented by blockchain technology. Blockchain flips the paradigm, replacing private ledgers with open, immutable digital trails that anyone can audit. Its decentralized architecture connects nodes into a fractal network, where each participant becomes both a custodian and a beneficiary. The liberated customer emerges as the centerpiece of this system, no longer beholden to intermediaries or hidden balances. Trust in this system is algorithmic, encoded in cryptographic proof rather than the shadowy guarantees of institutional elites.

The neural network diagram mirrors this philosophical evolution, portraying a cascade from the “world” layer to the “physical” layer. At the apex, the “Cosmos” and “Planet” nodes symbolize the foundational structures of existence, analogous to the overarching framework of centralized banks. The “Life” and “Ecosystem” nodes delve into perception and agency, capturing the biological and sociological interplay that sustains human engagement with systems. Here lies the heart of the conflict: the “Generative” nodes—Ratio, Competition, and Odds—epitomize the mechanisms by which value is contested and created. The “Cartel” node, colored paleturquoise, represents stability but also a limitation of freedom, clashing with the emergent dynamism of blockchain.

At the bottom of the diagram, the “Physical” layer embodies a spectrum ranging from volatility and the unknown to stability and freedom. These nodes reflect the potential of blockchain to destabilize entrenched systems while offering a new equilibrium grounded in transparency and collective agency. The Red Queen hypothesis, symbolized by the sacrificial dynamics of Prometheus, underscores the perpetual race between innovation and co-option. Blockchain, as the Promethean force, sacrifices stability to ignite a volatile but generative ecosystem.

In visualizing this neural network, the conceptual trajectory from private to public infrastructures becomes clear. Each node and edge serves as a metaphor for the transition from opaque cartel operations to an open, trustless economy. This is not merely a technological shift but a philosophical one, redefining the relationship between individuals, institutions, and the networks that bind them. The blockchain network, much like a neural network, thrives on connections and feedback, weaving individual contributions into a resilient, decentralized whole. The title “Bitcoin” atop the diagram serves as a beacon of this transformation, encapsulating both the promise and the peril of a liberated financial future.

Show code cell source Hide code cell source

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

# Define the neural network fractal
def define_layers():
    return {
        'World': ['Cosmos', 'Planet', 'Life', 'Ecosystem', 'Generative', 'Cartel', ], ## Cosmos, Planet
        'Perception': ['Perception'], # Life
        'Agency': ['Hustle', 'Narrative'], # Ecosystem (Beyond Principal-Agent-Other)
        'Generative': ['Ratio', 'Competition', 'Odds'], # Generative
        'Physical': ['Volatile', 'Unknown',  'Freedom', 'Known', 'Stable'] # Physical
    }

# Assign colors to nodes
def assign_colors():
    color_map = {
        'yellow': ['Perception'],
        'paleturquoise': ['Cartel', 'Narrative', 'Odds', 'Stable'],
        'lightgreen': ['Generative', 'Competition', 'Known', 'Freedom', 'Unknown'],
        'lightsalmon': [
            'Life', 'Ecosystem', 'Hustle', # Ecosystem = Red Queen = Prometheus = Sacrifice
            'Ratio', 'Volatile'
        ],
    }
    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=9, connectionstyle="arc3,rad=0.2"
    )
    plt.title("Bitcoin", fontsize=15)
    plt.show()

# Run the visualization
visualize_nn()

Fig. 6 So we have a banking cartel, private ledgers, balancing payments, network of banks, and satisfied customer. The usurper is a public infrastructure, with open ledgers, digital trails, block-chain network, and liberated customer