Stable

Fig. 37 There’s a demand for improvement, a supply of product, and agents keeping costs down through it all. However, when product-supply is manipulated to fix a price, its no different from a mob-boss fixing a fight by asking the fighter to tank. 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()

Fig. 38 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%)