Orient

The neural network fractal described in the code transcends its mathematical and graphical representation, serving as a profound commentary on the structure and dynamics of human existence, agency, and the cosmos. At its core, it mirrors the layered complexity of life, mapping out an interconnected hierarchy of values, forces, and choices. Each layer, from “World” to “Physical,” captures essential themes in human and cosmic narratives, from entropy and needs to freedom and stability. The deliberate progression through these layers reflects a journey from abstract universals to tangible lived experiences.

The “World” layer sets the stage by encapsulating the raw, fundamental forces governing existence—entropy, ecosystems, and the dualities of generative and exploitative systems. It frames the universe not as a static entity but as a battleground of opposites: creation versus destruction, necessity versus excess, and survival versus collapse. This tension feeds into the “Perception” layer, where the ledger metaphor suggests a divine or universal judgment, a reckoning of actions and consequences across time and space. This intermediary space between chaos and agency ties the cosmic to the personal, imbuing decisions with weight.

Fig. 34 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.

The “Agency” layer represents a pivotal juncture where human choices diverge between openness and trust, good and evil. Here, the fractal becomes deeply symbolic of the human condition—each node a reflection of moral dilemmas and the compromises that shape civilizations. The presence of “Generative” and “Physical” layers beneath highlights the practical outcomes of these moral struggles, where dynamics of competition, tokenization, and monopolization interplay with revolutionary volatility, resentment, and moments of jubilee.

Color coding in the network adds an evocative layer of meaning, resonating with symbolic archetypes. The yellows of perception suggest enlightenment and clarity, while the greens of generative mechanisms point to vitality and progress tinged with compromise. Turquoise and salmon hues, with their associations of oppression and sacrifice, underline the cyclical nature of power and resistance in historical and social contexts.

The code’s architecture, much like the fractal it visualizes, reinforces an ethos of inversion as transformation. By automating connections between layers, it echoes the deterministic yet emergent nature of human systems, where each layer feeds into the next, both shaping and being shaped by it. The graph is more than a visual aid; it is a narrative device, tracing the arc of history, philosophy, and individual will. The title, “Inversion as Transformation,” aptly captures the essence of this dynamic interplay. It is through inversions—shifts in power, perspective, and equilibrium—that the system evolves, finding moments of stability in its ceaseless flux.

Ultimately, this neural network is not merely a computational exercise; it is a philosophical blueprint. It invites viewers to reflect on their place within the vast lattice of existence and agency, to consider how their actions resonate across layers, and to find meaning in the interplay of order and chaos, freedom and constraint, entropy and renewal. This fractal becomes a lens for understanding life as a dance of interconnected forces, a tapestry woven from the threads of cosmic, social, and personal dynamics.

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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': ['Cosmos-Entropy', 'Planet-Tempered', 'Life-Needs', 'Ecosystem-Costs', 'Generative-Means', 'Cartel-Ends', ], # Theomarchy, Mortals, Fire
        'Perception': ['Perception-Ledger'], # God
        'Agency': ['Open-Nomiddleman', 'Closed-Trusted'], # Evil & Good
        'Generative': ['Ratio-Weaponized', 'Competition-Tokenized', 'Odds-Monopolized'], # Dynamics, Compromises
        'Physical': ['Volatile-Revolutionary', 'Unveiled-Resentment',  'Freedom-Dance in Chains', 'Exuberant-Jubilee', 'Stable-Conservative'] # Values
    }

# Assign colors to nodes
def assign_colors():
    color_map = {
        'yellow': ['Perception-Ledger'], # , Judgement Day, Key
        'paleturquoise': ['Cartel-Ends', 'Closed-Trusted', 'Odds-Monopolized', 'Stable-Conservative'], # Slavery, Colonialism, Worker
        'lightgreen': ['Generative-Means', 'Competition-Tokenized', 'Exuberant-Jubilee', 'Freedom-Dance in Chains', 'Unveiled-Resentment'], # Das Kapital, Frankenstein, AI
        'lightsalmon': [
            'Life-Needs', 'Ecosystem-Costs', 'Open-Nomiddleman', # Ecosystem = Red Queen = Prometheus = Sacrifice
            '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=9, connectionstyle="arc3,rad=0.2"
    )
    plt.title("Inversion as Transformation", fontsize=15)
    plt.show()

# Run the visualization
visualize_nn()

Fig. 35 Terra, Celsius, FTX. Contemplate the following: world (twitter), money (terra), bank (celsius), exchange (ftx), yields (hedgefunds). IT’S A REALLY, surprisingly user-friendly experience,” says Stephen Askins, a shipping lawyer, of his interactions with the Houthis, the militia that has been attacking commercial ships in the Red Sea for more than a year. “You write to them, respectfully. They write back, respectfully, and wish you a happy passage.” Source: Economist

1. Entropy, Gravity: Founded in Berkeley & setup in Hongkong -> Bahamas -> US?

   • Gate: everyone is within the gates, perfect information, fixed odds

   • Coin toss, Dice roll, Roulette spin, Bespoke regulation?

2. Patterns: Obsessed with risk, solving puzzles, Maths from MIT

   • Key: only you are in and others speculate, asymmetric information, wild odds

   • Poker, Blockchain, Untrusted (Sam Blankman-Fried “sold” trust instead of openness)?

3. Connotation: Got kapital from family & later market

   • Entrants: with their exits and entrances, uncertain odds

   • Horse racing, DC regulation would give access to Wallstreet?

4. Interaction: US-Japan arbitrage on crypto pricing

   • Stable-Diffusion: weaponized, tokenized, monopolized access-to-key, conditional odds

   • Red Queen, Exchanges, FTX (nested within Alameda; same people; monopoly-delusion)

5. Tendency: Innocuous name: Alameda Research vs. FTX

   • Optimization: volatility, uncertainty, freedom, certainty, stability

   • Victorian vs. Coen Brothers, Morality vs. Aesthetics, Teleology vs. Eternal Return

odds ~ resources ~ tokens

• Fixed for Bitcoin

• Out of thinair for FTX

• Alameda borrows from FTX with FTT as collateral (when lenders test the waters out of suspicion)

• Then Sam Bankman-Fried becomes JP-Morgan of crypto

  • Crypto-bro of last resort

  • Bailing out the ecosystem

  • Instead of going into survival mode

“TO DEMAND moral purpose from the artist is to make him ruin his work,” said Goethe. Once, I would have defended that statement as if it were an article of religion. Now, having reached the end of my own brief memoir, I find the Victorian in me will not be satisfied without a moral—or perhaps, it is fairer to say, a conclusion. And since I am writing this to please no one but myself, a conclusion is what I will damn well write.”

Excerpt From
The Various Flavors of Coffee
Anthony Capella
https://books.apple.com/us/book/the-various-flavors-of-coffee/id420768595
This material may be protected by copyright.

Layers/colors:

1. Grey/Cambridge: Aesthetic (100%)

2. Yellow/Wallstreet: Instant Gratification

3. Salmon/BayArea: Bracing for Worthy-Adversary

4. Paleturquoise/Oxford: Secured Cartel (Might makes right)

5. Lightgreen/LSE: Optimization, Morality, Teleology (5%-95%)