Transvaluation

A cadence is the bridge between aesthetics and ethics, between form and feeling, between structure and transformation. It is not merely the closing punctuation of a musical phrase but the very essence of movement itself—the delta of existence. It is the shift between emotional states, the traversal of nodes in the neural network of life. In music, cadences are recognized as harmonic resolutions, but their function extends far beyond sound. They exist in literature, in human psychology, in political history, in the hierarchies that govern our social and moral intuitions. Cadences dictate the rhythm of life itself, the way we perceive change, and how we reconcile disparate emotional states.

Liberation from the bondage of rebirth
– Larry

In music, cadences have traditionally been classified into four primary types—authentic, plagal, deceptive, and half—but this taxonomy is inadequate to describe the full range of emotional transitions that music can evoke. An authentic cadence, resolving from V to I, is the quintessential arrival at home, the fulfillment of expectation. The plagal cadence, IV to I, often associated with the “Amen” of church music, carries a different emotional character—less triumphant, more subdued, a gentle assent rather than a triumphant declaration. The deceptive cadence, which leads the listener towards an expected resolution only to divert elsewhere (V to vi, for instance), is an exercise in suspended anticipation, a harmonic feint that mirrors the way in which life often denies us our anticipated conclusions. The half cadence, stopping at V, is the embodiment of unresolved tension, a dangling question mark awaiting its answer. Yet even these do not exhaust the range of cadences, because every harmonic move carries its own delta, its own emotional trajectory, whether subtle or dramatic. The movement from vi to V in the Mixolydian mode is a cadence of its own kind, one that teeters on the edge of finality but never quite arrives at the sense of closure provided by the major tonic.

Beyond music, cadences structure the way we experience emotion itself. Every shift from sorrow to relief, from tension to relaxation, from love to despair, is a cadence. Take, for example, the phenomenon of Schadenfreude, the uniquely human experience of taking pleasure in another’s misfortune. It is, at its core, a cadence of hierarchical contrast, a shift from witnessing another’s suffering (a moment of tension or tragedy) to the release of pleasure in realizing that we are, by comparison, in a superior position. Unlike musical cadences, which are dictated by harmonic relationships, Schadenfreude is an entirely internal cadence, orchestrated in the mind of the observer. It is an emotional deception—a kind of deceptive cadence in the moral realm—because it does not grant true resolution, only the illusion of it. The pleasure is fleeting, built on a hierarchical juxtaposition that does not actually improve one’s own condition but merely changes the reference point. Nietzsche understood this deeply: the will to power thrives on such cadences, on the constant reordering of status, the shifting of dominance and submission, the recalibration of relative positions within the human hierarchy.

Fig. 17 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.

Cadences also shape narrative. A great novel is built on cadential shifts in mood, tone, and tension. The tragic arc of Shakespeare’s King Lear is structured by emotional cadences—Lear moves from power to vulnerability, from rage to clarity, from self-deception to self-recognition. The catharsis of tragedy is itself a cadence: the audience moves from witnessing suffering to experiencing an emotional release, a transfiguration of pain into meaning. Even comedic structures rely on cadence, the tension of anticipation resolved by the punchline. Laughter, after all, is a kind of cadence, a sudden emotional drop from the expectation of seriousness to the unexpected absurdity of reality.

History, too, is shaped by cadences. Revolutions do not emerge in a linear progression but in sudden harmonic shifts—violent upheavals, ideological realignments, the abrupt movement from stability to chaos and back again. The French Revolution is a deceptive cadence in historical form: the expected resolution of liberty and equality never quite arrives as anticipated, instead leading to the Napoleonic Empire, a resolution both triumphant and compromised. Political rhetoric operates on cadences as well; the best orators understand the emotional swells and releases necessary to guide an audience through conviction and doubt, outrage and resolution.

Even in individual consciousness, life is experienced as a series of cadences. No emotion is static, no state of mind is permanent. We move from anxiety to peace, from love to indifference, from confidence to doubt in a constant interplay of internal resolutions and suspensions. Depression, for instance, is a half cadence stretched indefinitely, a phrase left unresolved, a harmonic expectation that never finds its home. Euphoria, on the other hand, is an authentic cadence, the rare moments when all elements align and the sense of arrival is unmistakable.

To live is to navigate cadences. Every decision we make, every interaction we have, every shift in our internal state follows the logic of movement between nodes. This is why music resonates so deeply with human emotion—it is a model of existence itself, a compression of life’s fundamental structure into sound. A cadence is never merely an ending; it is the architecture of change, the way we move through time, the syntax of the human condition.

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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', 'World-Tempered', 'Ucubona-Needs', 'Ecosystem-Costs', 'Space-Trial & Error', 'Time-Cadence', ], # Veni; 95/5
        'Mode': ['Ucubona-Mode'], # Vidi; 80/20
        'Agent': ['Oblivion-Unknown', 'Brand-Trusted'], # Vici; Veni; 51/49
        'Space': ['Ratio-Weaponized', 'Competition-Tokenized', 'Odds-Monopolized'], # Vidi; 20/80
        'Time': ['Volatile-Transvaluation', 'Unveiled-Resentment',  'Freedom-Dance in Chains', 'Exuberant-Jubilee', 'Stable-Victorian'] # Vici; 5/95
    }

# Assign colors to nodes
def assign_colors():
    color_map = {
        'yellow': ['Ucubona-Mode'],  
        'paleturquoise': ['Time-Cadence', 'Brand-Trusted', 'Odds-Monopolized', 'Stable-Victorian'],  
        'lightgreen': ['Space-Trial & Error', 'Competition-Tokenized', 'Exuberant-Jubilee', 'Freedom-Dance in Chains', 'Unveiled-Resentment'],  
        'lightsalmon': [
            'Ucubona-Needs', 'Ecosystem-Costs', 'Oblivion-Unknown',  
            'Ratio-Weaponized', 'Volatile-Transvaluation'
        ],
    }
    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'))   

    # 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("Veni, Vidi, Vici", fontsize=15)
    plt.show()

# Run the visualization
visualize_nn()

Fig. 18 Nvidia vs. Music. APIs between Nvidias CUDA & their clients (yellowstone node: G1 & G2) are here replaced by the ear-drum & vestibular apparatus. The chief enterprise in music is listening and responding (N1, N2, N3) as well as coordination and syncronization with others too (N4 & N5). Whether its classical or improvisational and participatory, a massive and infinite combinatorial landscape is available for composer, maestro, performer, audience. And who are we to say what exactly music optimizes?