Traditional

Joe Rogan occupies a peculiar space in the cultural ecosystem—a kind of High Priest of the podcasting world, where authority is conferred not through knowledge, expertise, or intellectual rigor, but through the sheer force of opinion. He does not explicitly identify with MAGA, nor does he pledge allegiance to any political movement, yet his podcast functions as a conduit for the same kinds of anti-establishment, anti-mainstream sentiments that define the MAGA ethos. His role is both shamanic and paradoxical: he claims no special insight, no grand theory of the world, yet he presides over an endless stream of conversations where strong opinions—untethered to evidence, consistency, or even curiosity—take precedence over critical thought. The guests may shift, the topics may range from the trivial to the conspiratorial, but the format remains constant: a casual, freewheeling space where the rejection of mainstream narratives is paramount, even as a new kind of ideological conformity takes shape.

There is an illusion at the heart of this world—a belief in radical independence of thought, in the interrogation of received wisdom, in the virtue of questioning everything. And yet, the behaviors of this subculture are anything but independent. Instead, they move in eerie unison, a flock responding to unseen signals, shifting en masse toward the latest obsession, the latest controversy, the latest grand narrative of oppression, corruption, and elite deception. If one voice in this world fixates on the Kennedy family as a symbol of deep-state intrigue, soon the entire flock echoes the sentiment. If the crisis of the day involves some perceived overreach of government power, the script spreads like wildfire. The coordination is near-perfect, but there is no central command, no explicit orders. It is a strange, self-organizing system, a kind of decentralized orthodoxy that follows its own rhythms of agitation and revelation.

Fig. 36 Akia Kurasawa: Why Can’t People Be Happy Together? This was a fork in the road for human civilization. Our dear planet earth now becomes just but an optional resource on which we jostle for resources. By expanding to Mars, the jostle reduces for perhaps a couple of centuries of millenia. There need to be things that inspire you. Things that make you glad to wake up in the morning and say “I’m looking forward to the future.” And until then, we have gym and coffee – or perhaps gin & juice. We are going to have a golden age. One of the American values that I love is optimism. We are going to make the future good.

The rejection of mainstream media—dismissed wholesale as “fake news”—only reinforces this closed-loop system. They see themselves as liberated from propaganda, as truth-seekers navigating the world with unfiltered clarity, and yet their patterns of belief and outrage are predictable, synchronized, and strangely uniform. This is not the freedom of thought they claim to embody; it is something closer to an echo chamber, a new kind of doctrinal certainty masquerading as skepticism.

Joe Rogan, for all his detachment from formal ideology, plays an instrumental role in this phenomenon. He smokes with his guests, or at least allows them the space to partake, creating an environment of relaxation, informality, and open exchange that gives the illusion of boundless possibility. But what emerges from these conversations is rarely unpredictable. It is not an exploration of the unknown, but a ritual performance of contrarianism—a reaffirmation of the belief that “the system” is rigged, that expertise is suspect, that the mainstream has failed, and that the real truth lies somewhere out on the fringes. It is, in many ways, an anti-intellectual project, one that elevates instinct over analysis, opinion over knowledge, and a vague sense of persecution over concrete understanding.

In this world, to “not know” is not a limitation but a credential. To admit ignorance is not the first step toward learning but a badge of authenticity, a proof of one’s distance from the corrupted institutions of knowledge. The power of the podcast format in this space is that it creates the appearance of raw, unfiltered access to reality—long, unedited conversations that feel more “real” than the soundbites and polished narratives of traditional media. But beneath this façade of openness, the range of ideas remains narrow, the patterns of thought strikingly rigid. There is a lockstep quality to it all, a strange paradox where the rejection of authority leads not to intellectual freedom but to a new kind of groupthink, a conformity that operates under the banner of rebellion.

And so, even as Joe Rogan disclaims any allegiance to MAGA, even as he positions himself as an outsider to political movements, the gravitational pull of his world is undeniable. He and his guests circle the same themes, perform the same rituals of skepticism, draw from the same well of discontent. He does not need to be MAGA to be central to the broader project, to act as one of its primary architects. In the end, whether by design or by accident, he provides the scaffolding for a worldview that sees itself as untamed, unrestricted, and yet, in its own way, more predictable than the institutions it claims to resist.

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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. 37 While neural biology inspired neural networks in machine learning, the realization that scaling laws apply so beautifully to machine learning has led to a divergence in the process of generation of intelligence. Biology is constrained by the Red Queen, whereas mankind is quite open to destroying the Ecosystem-Cost function for the sake of generating the most powerful AI.