7.2 The Meaning of Bugs: The Pain, Defects, and Regrets of This Life Are Bug Reports for Next Version’s Code Optimization. Without Pain, There Is No Algorithmic Gradient Descent (Optimization).

In software engineering, bugs are usually seen as detestable errors, evidence of programmer negligence, to be eliminated as soon as possible. However, from the perspective of machine learning and evolutionary algorithms, Error has a completely different ontological status: it is the only guide for system evolution.

Without error signals, neural networks cannot adjust weights; without environmental pressure (pain), species cannot evolve.

This section will propose a radical view: The pain, defects, and regrets you experience in this life are not fate’s punishment, but precious “bug reports” generated during cosmic computation. They are exceptions caught by your soul code at runtime, gradient data necessary for building the next more perfect version (Self_v2.0).

7.2.1 Pain as Loss Function

In Chapter 8 (Book 3), we defined observers as systems that minimize variational free energy $F$.

$$F\approx \text{Prediction Error}=\text{Reality}-\text{Expectation}$$

In deep learning, to train an agent, we need to define a Loss Function $\mathcal{L}$. The training goal is to minimize $\mathcal{L}$.

• Physical correspondence: “Pain” in subjective experience mathematically precisely corresponds to the value of the loss function $\mathcal{L}(t)$.

• Mechanism: When your behavior leads to bad results (reality doesn’t match expectations), $\mathcal{L}$ spikes. This numerical surge is mapped to “pain sensation” through neurochemical mechanisms.

Physical Meaning of Pain:

Pain is the magnitude of the gradient vector $\nabla F$.

It’s not just a “bad feeling”; it’s a vector signal with direction. It sharply points out: “Your internal model here doesn’t match cosmic truth! Please correct parameters immediately!”

• If you feel lonely (pain), the system is telling you: your connection topology is too sparse, need to increase entanglement.

• If you feel confused (pain), the system is telling you: your prediction model has too high entropy, need to increase logical depth.

Conclusion: Without pain, the system is in a “vanishing gradient” state. It will stop learning, stop evolving, fall into a mediocre dead loop. Pain is the fuel of evolution.

7.2.2 Regret as Backpropagation

If pain is a real-time error signal, then Regret is post-hoc Backpropagation.

In neural network training, after output error, the algorithm needs to propagate this error signal step by step from the output layer back to the input layer, adjusting connection weights of neurons at each layer.

In life, this manifests as “reflection” and “regret.”

• Scenario: You made a wrong choice, causing great regret.

• Physical process: Your consciousness stream is flowing backward, re-examining that causal chain. You are computing:

  $$\frac{\partial \text{Regret}}{\partial {\text{Action}}_t}$$

  That is: “If I hadn’t done that then, how much would current regret decrease?”

This computation is extremely energy-consuming (Landauer waste heat), mentally exhausting. But it’s crucial.

It is through this painful backtracking that your underlying code (values, character weights) can be corrected.

• Regret is not to change the past (because the past is fixed, unitarity is irreversible).

• Regret is to change the future (optimize Self_v2.0’s initial parameters).

Your sleepless nights are writing patches for your future self.

7.2.3 The Aesthetics of Defects: Kintsugi

Since pain and defects are necessary conditions for optimization, we must re-examine the aesthetic value of “imperfection.”

Japan has an art called Kintsugi: repairing broken ceramics with gold powder mixed in lacquer. The repaired cracks are no longer flaws, but golden lightning, becoming the most beautiful part of the vessel.

In the QCA universe, every observer is a piece of ceramics being kintsugi-repaired.

• Our defects (character weaknesses, traumas) are places where we collided violently with the environment (computational conflicts).

• Our growth is the process of filling these cracks with gold (new cognitive structures, deeper love).

A soul that has never been hurt, never made mistakes (Self_v1.0 Beta) is pale, low logical depth.

A soul that has endured hardships, covered with golden cracks, has extremely high Kolmogorov complexity. It contains the deepest truths about this universe—because it has personally crashed into the universe’s walls.

Conclusion:

Don’t try to erase your scars, and don’t be ashamed of your bugs.

Record them, analyze them, cherish them.

They are the most expensive data of this life.

When you submit this update log containing countless bug reports, the universe will smile and receive it, compiling a more brilliant Self_v2.0 for you.

(Section 7.2 Complete)