Revolution

Dodgson

In the grand architecture of classical storytelling, the strategic bequest motive emerges as the silent force weaving together ambition, legacy, and the fragility of human plans. This motive, the transference of value—whether material, moral, or symbolic—between generations or agents, lies at the heart of many tragedies. Its brilliance is not in its explicitness but in the ways it is subverted, ambushed, or gamed. Stories of this caliber are not content with smooth successions; they demand disruptions that transform inheritance into a battlefield for agency, fate, and human frailty.

In Hamlet, the strategic bequest motive is nothing short of a battleground ambushed by circumstance and indecision. The rightful transference of the Danish throne is derailed by murder, deceit, and the young prince’s existential wrestling with the meaning of vengeance and legacy. Hamlet’s failure to execute his charge transforms the bequest motive into a tragedy of paralysis, where every decision reverberates with uncertainty. The kingdom itself becomes collateral, as if the throne were a poisoned chalice, unfit for rightful succession. Shakespeare’s brilliance lies in embedding this ambush within Hamlet’s mind, the true stage upon which the collapse of legacy plays out.

Fig. 21 What Exactly is Identity. A node may represent goats (in general) and another sheep (in general). But the identity of any specific animal (not its species) is a network. For this reason we might have a “black sheep”, distinct in certain ways – perhaps more like a goat than other sheep. But that’s all dull stuff. Mistaken identity is often the fuel of comedy, usually when the adversarial is mistaken for the cooperative or even the transactional.

In Macbeth, by contrast, the strategic bequest motive is hacked—violently and deliberately—by external forces cloaked in ambiguity. The three witches, agents of chaos, infect Macbeth’s ambition with the idea of an impossible legacy: a kingship that he can seize but cannot pass on. The prophecy’s brilliance lies in its cruelty; it offers Macbeth a fleeting triumph at the expense of an enduring lineage. This hacking of the bequest motive reveals the fragility of human agency when confronted by the paradox of a poisoned gift: power gained but never secured. Macbeth’s dynasty is not merely doomed but foreclosed by design, exposing the hollowness of his blood-soaked ascent.

King Lear shifts the focus to the procedure itself, making the strategic bequest motive painfully explicit. Lear’s tragic flaw is not his desire to pass on his legacy but his method of doing so, dividing his kingdom among his daughters based on a hollow contest of flattery. The procedure, rooted in vanity rather than merit, turns his legacy into a weapon wielded against him. Lear’s madness, then, is the natural consequence of his failure to anticipate the fragility of his bequest plan. In exposing the procedural flaws of inheritance, Shakespeare lays bare the human tendency to confuse control with permanence, as if a signature or decree could secure an unbroken legacy in a world rife with chaos.

In Yellowstone, the strategic bequest motive is rendered as a sprawling epic of modern Americana, where the Dutton family’s ranch symbolizes the ultimate legacy under siege. Here, the bequest is not merely a question of bloodline or will but of cultural survival in a landscape increasingly hostile to tradition. Forces beyond the Duttons—corporate greed, political machinations, and environmental change—threaten the rug that ties the series together: the land itself. What makes Yellowstone compelling is its recognition of the broader principal-agent dynamics at play. The Duttons are not merely defending a family legacy but engaging in a war of gamification, where every actor—worker, agent, or rival—plays a role in determining the ranch’s fate. Victory, in this context, is not a guarantee but a tenuous gamble, a fragile equilibrium that underscores the vulnerability of legacy in a world driven by competition and exploitation.

What these narratives share is an understanding that the strategic bequest motive is never simple or straightforward. It is a space where human intention collides with the unpredictability of external forces, where the desire for continuity is ambushed, hacked, or undone by flawed procedures and unforeseen disruptions. In these stories, legacy is not a gift but a struggle, a reminder that what we seek to leave behind is often shaped as much by failure as by success. The yellow node, then, serves as a symbol of this liminal space—an intersection where inheritance and individuality meet, forever threatened by forces beyond our control.

Jobs

The statement positions networks and supply in contrasting roles: networks as evidence of demand, and supply as evidence of generativity. To decode this, one must first consider what a network represents. A network exists because of interconnected needs or desires—it emerges as individuals, organizations, or entities seek access, exchange, or collaboration. A network doesn’t materialize in a vacuum; it forms because there is demand for its existence, whether that demand stems from a shared interest, a flow of resources, or the need for communication. For instance, the strength of social media platforms like Twitter or professional networks like LinkedIn lies in their proof of demand—millions of users actively seek connection, information, or opportunities, and their collective engagement is the network’s lifeblood. Without this demand, a network would wither into irrelevance.

Supply, by contrast, is an act of creation. It doesn’t presuppose demand in the same way a network does. Generativity is the quality of being able to produce or originate, and supply embodies this principle. A baker, for example, produces bread regardless of whether a hundred customers are waiting at the door. The act of supplying is inherently generative; it brings something into existence that wasn’t there before. This doesn’t mean that supply and demand are divorced from one another, but rather that supply can often run ahead of demand—creating potential where none existed, sparking latent needs, or inspiring new forms of consumption.

The distinction between these two ideas is particularly crucial in fields like innovation or economic development. Proof of demand, as evidenced by a thriving network, reveals what people actively seek or need—it’s an observable metric of human desire or necessity. On the other hand, proof of supply’s generativity lies in its ability to create possibilities. A network responds to an already-present need, but supply can generate entirely new needs by introducing something novel or unforeseen. When Apple introduced the iPhone, for example, it wasn’t responding to demand for a smartphone—it was acting out of generativity, creating a supply that would later define and reshape the networks of demand around it.

Thus, demand binds networks to the present, reflecting what people value or prioritize in the moment. Generativity, however, allows supply to leap into the future, proposing what could be valuable, even before it is widely recognized as such. In this way, networks and supply form a dynamic interplay: networks anchor us to the currents of existing demand, while supply drives the possibilities that expand those networks into uncharted territories.

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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', ], # Polytheism, Olympus, Kingdom
        'Perception': ['Perception-Ledger'], # God, Judgement Day, Key
        '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'],
        'paleturquoise': ['Cartel-Ends', 'Closed-Trusted', 'Odds-Monopolized', 'Stable-Conservative'],
        'lightgreen': ['Generative-Means', 'Competition-Tokenized', 'Exuberant-Jubilee', 'Freedom-Dance in Chains', 'Unveiled-Resentment'],
        '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("Through the Looking Glass", fontsize=15)
    plt.show()

# Run the visualization
visualize_nn()

Fig. 22 Psilocybin is itself biologically inactive but is quickly converted by the body to psilocin, which has mind-altering effects similar, in some aspects, to those of other classical psychedelics. Effects include euphoria, hallucinations, changes in perception, a distorted sense of time, and perceived spiritual experiences. It can also cause adverse reactions such as nausea and panic attacks. In Nahuatl, the language of the Aztecs, the mushrooms were called teonanácatl—literally “divine mushroom.” Source: Wikipedia