Cosmic#

Here’s an essay that integrates the orchestrion automaton unveiled by Robert de La Chesnaye, its faltering performance, and its philosophical significance, as outlined in the French Studies article. This essay also contextualizes the orchestrion within Lacan’s automaton versus tuchē and Deleuze’s filmic “crack,” emphasizing the Frenchness of this intellectual heritage:


The Orchestrion, Automatism, and the Deathly Repetition of Rules#

Jean Renoir’s La Règle du jeu (1939) achieves a profound synthesis of art, philosophy, and mechanization through its representation of automata, most notably the orchestrion unveiled by Robert de La Chesnaye. Far from being a mere display of eccentric aristocratic decadence, the orchestrion emerges as a central symbol of alienation, repetition, and the collapse of an anachronistic class system. This essay situates the orchestrion within the broader intellectual frameworks of Lacan, Deleuze, and Walter Benjamin, underscoring its resonance with the philosophical underpinnings of French modernity.

The Orchestrion: A Mechanized Allegory#

The orchestrion, the crowning piece of Robert’s collection, is a marvel of mechanical ingenuity—a self-playing machine that embodies the alienated, performative existence of its owner and his class. Unlike the mechanical piano or the airplane seen earlier in the film, the orchestrion is a symbolic automaton that reflects not progress or freedom but stasis and decay. Its faltering performance during its grand unveiling encapsulates the inability of the pseudo-aristocracy to adapt to modernity or even to sustain the facade of their own rules.

This moment aligns with Lacan’s distinction between automaton (the predictable, mechanical repetition of events) and tuchē (the encounter with chance or the real). The orchestrion’s failure reveals a crack in the automaton’s seamless operation—a moment of tuchē that exposes the moribund state of its world. The machine’s inability to play its programmed music mirrors the aristocracy’s failure to perform the roles dictated by their social rules, signaling their imminent obsolescence.

Deleuze’s Crystal and the Crack#

Deleuze’s concept of the “crack” in the filmic crystal, drawn from his work on cinema, illuminates the orchestrion’s symbolic role. The orchestrion is a crystal-image par excellence: a self-contained machine that compresses time (the music of the past) into the present moment, repeating its performance ad infinitum. Yet, the crack that emerges during its malfunction disrupts this seamless temporality, introducing a rupture that destabilizes the illusion of permanence.

This crack reveals the orchestrion—and by extension, the aristocracy it represents—as incapable of renewal. It is a machine of pure repetition, performing without generativity or creativity. In this sense, Renoir critiques not only the aristocracy’s detachment but also their relationship to technology, which lacks the organic, adaptive qualities seen in other representations of human-machine interaction.

Automatism, Alienation, and Benjamin#

Walter Benjamin’s theses on history and mechanical reproduction provide a powerful lens for interpreting the orchestrion. Benjamin viewed modernity as a site of alienation, where technological reproduction strips objects of their aura and humans of their agency. The orchestrion epitomizes this dynamic: it is a machine that reproduces music mechanically, devoid of the soul and spontaneity of human performance.

Yet, Renoir complicates this critique by embedding the orchestrion within a cinematic narrative that itself relies on technological reproduction. This reflexivity mirrors Benjamin’s ambivalence toward film as a medium—its potential to democratize art is shadowed by its role in perpetuating alienation. The orchestrion thus becomes a meta-commentary on Renoir’s own medium, a machine that, like cinema, compresses time but risks falling into mechanical repetition.

Frenchness and Philosophical Resonance#

The orchestrion’s symbolism is deeply rooted in the French intellectual tradition. Descartes’ concept of the animal-machine finds new life in Renoir’s depiction of automata, reframed as indexes of a class system that treats both humans and machines as instruments of performance. This Cartesian inheritance is further filtered through Lacan’s psychoanalytic lens and Deleuze’s philosophy of cinema, creating a uniquely French synthesis of rationalism and existentialism.

Moreover, the orchestrion’s eighteenth-century aesthetic evokes the Enlightenment’s ambivalent legacy: its faith in reason and progress clashes with its role in perpetuating systems of oppression and alienation. Renoir’s orchestrion is both a tribute to and a critique of this legacy, a mechanized relic that embodies the contradictions of the modern age.

Closing: The Deathly Dance of Rules#

The orchestrion in La Règle du jeu is more than a machine—it is a symbol of the deathly repetition that governs the pseudo-aristocracy’s existence. Its faltering performance exposes the fragility of their world, shattering the illusion of order and permanence. Through the orchestrion, Renoir captures the essence of French modernity: a dance between reason and chaos, repetition and rupture, rule and exception.

By embedding this automaton within his cinematic tapestry, Renoir not only critiques the alienation of his era but also anticipates the philosophical and technological questions that continue to define ours. The orchestrion’s deathly music echoes across time, reminding us that the rules of the game are never as immutable as they seem.

Hide code cell source
import numpy as np
import matplotlib.pyplot as plt
import networkx as nx

# Define the neural network structure
def define_layers():
    return {
        'World': ['Cosmos', 'Earth', 'Life', 'Cost', 'Parallel', 'Time'], # Divine: Cosmos-Earth; Red Queen: Life-Cost; Machine: Parallel-Time
        'Perception': ['Perspectivism'],
        'Agency': ['Surprise', 'Optimism'],
        'Generativity': ['Anarchy', 'Oligarchy', 'Monarchy'],
        'Physicality': ['Dynamic', 'Partisan', 'Common Wealth', 'Non-Partisan', 'Static']
    }

# Assign colors to nodes
def assign_colors(node, layer):
    if node == 'Perspectivism':
        return 'yellow'
    if layer == 'World' and node in [ 'Time']:
        return 'paleturquoise'
    if layer == 'World' and node in [ 'Parallel']:
        return 'lightgreen'
    if layer == 'World' and node in [ 'Cosmos', 'Earth']:
        return 'lightgray'
    elif layer == 'Agency' and node == 'Optimism':
        return 'paleturquoise'
    elif layer == 'Generativity':
        if node == 'Monarchy':
            return 'paleturquoise'
        elif node == 'Oligarchy':
            return 'lightgreen'
        elif node == 'Anarchy':
            return 'lightsalmon'
    elif layer == 'Physicality':
        if node == 'Static':
            return 'paleturquoise'
        elif node in ['Non-Partisan', 'Common Wealth', 'Partisan']:
            return 'lightgreen'
        elif node == 'Dynamic':
            return 'lightsalmon'
    return 'lightsalmon'  # Default color

# Calculate positions for nodes
def calculate_positions(layer, center_x, offset):
    layer_size = len(layer)
    start_y = -(layer_size - 1) / 2  # Center the layer vertically
    return [(center_x + offset, start_y + i) for i in range(layer_size)]

# Create and visualize the neural network graph
def visualize_nn():
    layers = define_layers()
    G = nx.DiGraph()
    pos = {}
    node_colors = []
    center_x = 0  # Align nodes horizontally

    # Add nodes and assign positions
    for i, (layer_name, nodes) in enumerate(layers.items()):
        y_positions = calculate_positions(nodes, center_x, offset=-len(layers) + i + 1)
        for node, position in zip(nodes, y_positions):
            G.add_node(node, layer=layer_name)
            pos[node] = position
            node_colors.append(assign_colors(node, layer_name))

    # Add edges (without weights)
    for layer_pair in [
        ('World', 'Perception'), ('Perception', 'Agency'), ('Agency', 'Generativity'), ('Generativity', 'Physicality')
    ]:
        source_layer, target_layer = layer_pair
        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=10, connectionstyle="arc3,rad=0.1"
    )
    plt.title("Snails Pace vs. Compressed Time", fontsize=15)
    plt.show()

# Run the visualization
visualize_nn()
../../_images/b8238d80ec1e4d6147a86d3e87a244bbe54b24c4ee102f00fe0e0ccfc2e0292c.png
act3/figures/blanche.*

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?#

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