Resource#
Critique of Wall Street Through the World Layer Framework#
In the World Layer, Wall Street operates within the interplay of Cosmos, Earth, Life, Cost, Parallel, and Time, reflecting humanityâs shifting relationship with its origins, tools, and sacrifices. The treatment of Cost by Wall Street provides a stark illustration of how the modern world abstracts and perpetuates the ancient logic of the Red Queen.
Cost as Sacrifice in Red Queen Terms#
From the perspective of the Red Queen, survival requires relentless competition. Life itself operates under this principleâspecies evolve through continuous adaptation, often at the expense of others. Sacrifice, whether of time, resources, or lives, is inherent to this dynamic.
Wall Street adopts this Red Queen logic when it prioritizes cost-cutting as a mechanism for competitive advantage. Cutting costs, especially labor, becomes the modern equivalent of sacrifice, with human beings reduced to expendable resources in the pursuit of efficiency and profit.
Cutting Cost = Cutting People:
A rise in share prices is often celebrated after mass layoffs, but what is this if not a ritualistic offering to the market gods?
Humanity, once a direct participant in production, is now tokenized and devalued in a system that views labor as an inefficiency to be eliminated.
This is no different from ancient sacrifices, except that Wall Street obscures the bloodshed by wrapping it in the language of metrics and growth.
Life and Cost: The Red Queenâs Dance#
The nodes of Life and Cost embody the Red Queen, perpetuating a cycle of survival at all costs. Wall Street magnifies this by transforming humanityâs collective effort into abstracted numbers:
Life as Commodity:
Human lives are tokenized as âcosts,â stripped of individuality and framed as obstacles to profitability.
This reduction mirrors the biological competition inherent in the Red Queen dynamic, where entities must constantly cut, adapt, or perish.
Cost as the Driver of Sacrifice:
Wall Street doesnât just reflect the Red Queenâit actively accelerates it. Companies race to cut costs faster, automate quicker, and exploit more ruthlessly than their competitors, ensuring survival in a hostile financial ecosystem.
Cosmos and Earth: The Divine Disconnect#
In this framework, Cosmos and Earth represent divine or transcendent dimensionsâtimeless forces that ground humanity in something larger than itself. Wall Streetâs relentless focus on cutting costs reveals a profound disconnect from these divine nodes.
Cosmos (Ethics and Balance):
The cosmos invites reflection on balance, justice, and long-term sustainability. Wall Street, in its pursuit of immediate gains, ignores these considerations. Cutting costs may bolster short-term profits, but it often leads to long-term instabilityâeconomic, social, and even environmental.
Earth (Sustainability and Responsibility):
Earthly resources, including human labor, are finite. By treating cost-cutting as the ultimate goal, Wall Street disregards the physical and ecological limits of its actions. The divine node of Earth is sacrificed to the machine nodes of Parallel and Time, which demand constant efficiency and speed.
Parallel and Time: The Machine Logic#
Wall Streetâs focus on efficiency aligns it with the machine nodes of Parallel and Time. These nodes emphasize mechanized, algorithmic systems that prioritize speed and optimization over humanity.
Parallel:
Automation and digitization allow Wall Street to execute cost-cutting measures on an unprecedented scale. Labor once performed by humans is replaced by machines, intensifying the Red Queen dynamic by accelerating competition and eliminating human roles.
Time:
The pressure to deliver quarterly results traps companies in a perpetual sprint, where short-term gains outweigh long-term considerations. Time, compressed into financial quarters, becomes a weapon in the service of machine logic, leaving no room for reflection or ethical deliberation.
Wall Street as the Apex of the Red Queen#
Wall Street exemplifies the Red Queenâs logic by institutionalizing sacrifice within an abstract, mechanized framework. While ancient civilizations sacrificed individuals to appease divine forces, Wall Street sacrifices humanity to appease the marketâa god devoid of empathy or transcendence.
Human Cost: The logic of cutting costs echoes ancient rituals, but with no acknowledgment of humanityâs divine potential. Life is reduced to tokens, traded for fleeting financial gains.
Machine Supremacy: Parallel processing and time compression ensure that sacrifice is automated, stripping it of any human context or meaning.
Concluding Critique: A Red Queen Without Purpose#
Wall Streetâs treatment of cost reveals the dark heart of the Red Queen: relentless, competitive sacrifice without end or higher purpose. Unlike the divine nodes of Cosmos and Earth, which invite humanity to transcend its baser instincts, Wall Street perpetuates a cycle that is both dehumanizing and unsustainable.
While Wall Street claims to drive progress, its machine logic risks severing humanityâs connection to the divine and its own sense of purpose. In its pursuit of profit, it reduces life to a commodity, perpetuating a modern version of ancient sacrifice that reflects the worst excesses of the Red Queen dynamic.
Show code cell source
import numpy as np
import matplotlib.pyplot as plt
import networkx as nx
# Define the neural network structure; modified to align with "Aprés Moi, Le Déluge" (i.e. Je suis AlexNet)
def define_layers():
return {
'Pre-Input/World': ['Cosmos', 'Earth', 'Life', 'Nvidia', 'Parallel', 'Time'],
'Yellowstone/PerceptionAI': ['Interface'],
'Input/AgenticAI': ['Digital-Twin', 'Enterprise'],
'Hidden/GenerativeAI': ['Error', 'Space', 'Trial'],
'Output/PhysicalAI': ['Loss-Function', 'Sensors', 'Feedback', 'Limbs', 'Optimization']
}
# Assign colors to nodes
def assign_colors(node, layer):
if node == 'Interface':
return 'yellow'
if layer == 'Pre-Input/World' and node in [ 'Time']:
return 'paleturquoise'
if layer == 'Pre-Input/World' and node in [ 'Parallel']:
return 'lightgreen'
elif layer == 'Input/AgenticAI' and node == 'Enterprise':
return 'paleturquoise'
elif layer == 'Hidden/GenerativeAI':
if node == 'Trial':
return 'paleturquoise'
elif node == 'Space':
return 'lightgreen'
elif node == 'Error':
return 'lightsalmon'
elif layer == 'Output/PhysicalAI':
if node == 'Optimization':
return 'paleturquoise'
elif node in ['Limbs', 'Feedback', 'Sensors']:
return 'lightgreen'
elif node == 'Loss-Function':
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 [
('Pre-Input/World', 'Yellowstone/PerceptionAI'), ('Yellowstone/PerceptionAI', 'Input/AgenticAI'), ('Input/AgenticAI', 'Hidden/GenerativeAI'), ('Hidden/GenerativeAI', 'Output/PhysicalAI')
]:
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("Archimedes", fontsize=15)
plt.show()
# Run the visualization
visualize_nn()
Fig. 22 In the 2006 movie Apocalypto, a solar eclipse occurs while Jaguar Paw is on the altar. The Maya interpret the eclipse as a sign that the gods are content and will spare the remaining captives. Source: Search Labs | AI Overview#