Engineering#
The idiom âcoulda, woulda, shouldaâ encapsulates the essence of regret and unfulfilled potential, serving as a shorthand for the human tendency to dwell on missed opportunities and alternate paths. Its plaintive rhythm conveys both a wistful longing and a sense of futility, mirroring the structure of games and decisions governed by neuroarchitecture. By interpreting âcoulda, woulda, shouldaâ through the framework of fixed odds, pattern recognition, leveraged agency, curtailed agency, and spoils for further play, we uncover the deeper layers of human cognition that give this phrase its enduring resonance. Each word represents not just a lament but a reflection of the pathways we navigate, constrained and shaped by the rules of our inner and outer worlds.
Fixed Odds: The Immutable âCouldaâ#
âCouldaâ reflects the realm of possibility, the paths left untaken due to circumstances beyond our control. Fixed odds dominate this layer, as it is tied to external conditionsâchance encounters, timing, and the immutable rules of existence. In this sense, âcouldaâ is a coin toss that never landed in our favor, a roulette spin that passed us by. We dwell on these outcomes not because they were within our grasp but because they reveal the boundaries of what was ever possible.
This reflects the pre-input layer of the neural network, where immutable laws govern the initial conditions of our lives. Whether shaped by genetics, socioeconomic status, or historical context, these fixed odds form the scaffolding of our regrets. The missed opportunities of âcouldaâ remind us of the cold arbitrariness of lifeâs starting positions, where the cosmos, indifferent and unyielding, dictates the rules of the game.
Pattern Recognition: The Reflective âWouldaâ#
âWouldaâ shifts from possibility to hypothetical action, where patterns of causation and consequence dominate. This is the realm of recognition, where we replay scenarios in our minds, searching for the key moments when different choices might have led to different outcomes. âWouldaâ is the layer of internal logic, a retrospective map we construct to make sense of what could have been.
At this stage, we act as machine learners processing static datasets of memory and perception, identifying patterns and gaps. âIf only I had seen the signsâ or âif only I had acted soonerâ are echoes of this reflective exercise. The yellow node of perception, with its emphasis on extracting meaning from static information, governs this stage of regret. âWouldaâ is less about the external conditions of the world and more about the internal struggle to process and understand the patterns that shaped our lives.
Leveraged Agency: The Aspirational âShouldaâ#
âShouldaâ speaks to action deferred, the moments when agency was available but unrealized. Unlike the wistful âcouldaâ and contemplative âwoulda,â âshouldaâ carries a sharper stingâa moral or personal failure to act on the opportunities presented. This is the layer of leveraged agency, where human will, like the jockey guiding the horse, has the power to influence outcomes but falters.
Here lies the tragedy of unrealized potential. âShouldaâ represents the red queenâs domain, where agency is active but constrained by hesitation, fear, or doubt. It is the moment the predator misses its prey not because of external conditions but because it failed to strike at the right time. In human terms, this is the realm of procrastination, indecision, and moral compromise. âShouldaâ carries with it the weight of responsibility, a reflection of the missed chances where action was entirely within reach.
Curtailed Agency: The Acceptance of âCoulda, Woulda, Shouldaâ#
When combined, the three elements of the idiomââcoulda, woulda, shouldaââcollapse into curtailed agency, where the multiplicity of regrets becomes a static reality. This stage reflects the limits imposed by time, society, and the finite nature of human life. Once the moment has passed, the outcomes are fixed, and the individualâs agency becomes curtailed by the irreversibility of events.
This layer aligns with the hierarchical constraints of societal systems or the inevitability of mortality, where the vast possibilities of âcouldaâ and the intricate patterns of âwouldaâ are reduced to the cold finality of âtoo late.â Like cartels in sports or oligarchies in economics, this curtailed agency imposes a kind of stabilityâa bitter acceptance that the game is over, the odds are set, and no further play is possible.
Spoils for Further Play: Learning from Regret#
Despite its lamenting tone, âcoulda, woulda, shouldaâ contains within it the seeds of renewal. The spoils of regret are not material but experiential, offering a reservoir of lessons and insights for future decisions. The phrase invites reflection, not as a punishment but as an opportunity to reweight resources, recalibrate strategies, and emerge wiser.
This aligns with the emergent layer of the neural network, where past experiences feed into higher-order goals. Regret, when processed constructively, becomes the groundwork for new pathways and possibilities. The spoils of âcoulda, woulda, shouldaâ lie in its capacity to transform bitterness into resolve, disappointment into growth. The phrase, though backward-looking, carries a forward-looking promise: the chance to play the next round of life with greater clarity and purpose.
The Neuroarchitecture of Regret#
âCoulda, woulda, shouldaâ is more than an idiomâit is a distillation of the games we play within ourselves, governed by the layers of neuroarchitecture that shape our thoughts and actions. Fixed odds, pattern recognition, leveraged agency, curtailed agency, and spoils for further play are all present within its plaintive rhythm, compressing the complexity of human regret into three simple words.
At its heart, the idiom reminds us that regret is not just a burden but a reflection of our humanity. It mirrors our capacity for imagination, our yearning for agency, and our endless quest to make sense of a world that is, by its nature, uncertain. In the games of life, we cannot change the rules or replay the past, but we can carry forward the lessons of what could have been, what would have been, and what should have beenâtransforming regret into the fuel for what still might be.
Show 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', ],
'Perception': ['Perception'],
'Agency': ['Digital-Twin', 'Enterprise'],
'Generativity': ['Parasitism', 'Mutualism', 'Commensalism'],
'Physicality': ['Offense', 'Lethality', 'Retreat', 'Immunity', 'Defense']
}
# Assign colors to nodes
def assign_colors():
color_map = {
'yellow': ['Perception'],
'paleturquoise': ['Time', 'Enterprise', 'Commensalism', 'Defense'],
'lightgreen': ['Parallel', 'Mutualism', 'Immunity', 'Retreat', 'Lethality'],
'lightsalmon': [
'Cost', 'Life', 'Digital-Twin',
'Parasitism', 'Offense'
],
}
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("Photons & Divinity, Tryptophan & Red Queen, Silicon & Machine", fontsize=15)
plt.show()
# Run the visualization
visualize_nn()