If the Universe Were a Pretrained Model, How Would We Call Its API?

If the Universe Were a Pretrained Model, How Would We Call Its API?
# 43 Talks Salon: Ancient Wisdom Meets AI Thinking

At the **43 Talks** offline salon, conversations usually revolve around **technology, trends, and products**. But in a recent session, AIGC content creator **Tech Commander** — with 250,000 followers — shifted the focus in an entirely unexpected way.

> “Let me be clear—what I’m about to share has no scientific basis.”

Then, with a serious tone, he introduced *Xiuxian* — the ancient Chinese practice of "cultivating immortality."

This wasn’t superstition or parody. Instead, it evolved into **one of the most hard-core theoretical dissections of ancient wisdom**, reframed through the same cognitive tools we use to understand large AI models.

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## Diverging from Binary Thinking

![image](https://blog.aitoearn.ai/content/images/2025/11/img_001-474.jpg)

In this salon, the talk felt more like a **thousands-year-spanning thought experiment** than a tech presentation.  
Listeners were encouraged to:

- Suspend **binary thinking** (true vs. false, science vs. superstition)
- Ask deeper questions, such as:  
  **Is our scientific paradigm simply one possible model among many for understanding the world?**

![image](https://blog.aitoearn.ai/content/images/2025/11/img_002-443.jpg)

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## Prediction: Prompting the Universe’s Large Model

**Core question:** How could shaking a few copper coins make the universe “respond”?

Tech Commander's **bold hypothesis**:

1. **Universe as a Pre-trained Supermodel:**  
   - Parameters: Beyond any imaginable scale  
   - Dataset: Everything from the Big Bang to now  
   - Operation: Continuous, following unknown rules that “generate” reality

2. **Divination as Prompt Engineering:**  
   - Rituals provide structured input — time, location, ceremonial steps — targeting specific outputs
   - The hexagram becomes the **returned output tokens** from the model  
   - Not predicting a single future, but **sampling probabilities** across possible futures

3. **Practical Approach:**  
   - Avoid debating “is it scientific?”  
   - Instead ask: **Does it work?**  
   - Even if the model’s mechanics are a black box (like GPT writing poetry), repeated meaningful outputs make it a “usable technology”

![image](https://blog.aitoearn.ai/content/images/2025/11/img_003-419.jpg)
![image](https://blog.aitoearn.ai/content/images/2025/11/img_004-395.jpg)

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## Compute Power & Algorithms: Who Holds the API Key?

If the **universe is a large model**, who can run it and interpret its results?  
Tech Commander’s answer: it depends on **hardware** and **algorithms**.

### Hardware Hypothesis

- **Most brains** = CPUs (general-purpose, survival-focused processing)  
- **Some brains** = GPUs or TPUs (parallel computation, specialized processing)  
- This architecture may allow certain people to naturally process complex “universe model” outputs

![image](https://blog.aitoearn.ai/content/images/2025/11/img_005-356.jpg)

### Ancient Algorithms

- **Four Pillars of Destiny**, **Zi Wei Dou Shu** = optimized specialist models
- Iterated over centuries to accurately parse certain “data types” from the universe model
- When **high-end hardware** runs **refined algorithms**, exceptional insights can emerge

> Genius may not be divine inspiration — it might be advanced hardware running an as-yet-unmastered algorithm.

![image](https://blog.aitoearn.ai/content/images/2025/11/img_006-323.jpg)
![image](https://blog.aitoearn.ai/content/images/2025/11/img_007-307.jpg)

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## Life Optimization: From External Query to Internal Fine-Tuning

The most exciting extension of this thinking is **turning the model inward** — treating **yourself** as the most complex, yet accessible model.

### Cultivation as Self-Optimization

The Science Captain’s view: cultivation (*xiuxian*) = **deep optimization and fine-tuning of your life system**.

- **Default state:** Like a factory-preset model, basic functions only, no access to source code
- **Goal:** Gain higher system permissions and become your own “model trainer”

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### Key Process Stages

1. **Inner Observation**  
   Similar to **model interpretability**: turning inward to understand your body’s parameters and weights.

2. **Repairing Leaks & Transforming Desires**  
   Comparable to **model optimization/regularization**: limiting overfitting to external stimuli, redirecting energy toward improving core health and efficiency.

3. **Foundation Building**  
   Achieving a **low-consumption, high-efficiency, stable new version** of yourself.

![image](https://blog.aitoearn.ai/content/images/2025/11/img_008-286.jpg)

---

## Practical Links Between Ancient Theory and Modern Tools

Modern open-source platforms like [AiToEarn官网](https://aitoearn.ai/) reflect the same principles:

- **Hardware:** Our brains and devices  
- **Algorithms:** AI models and workflows  
- **Model:** Integrated systems for creation and monetization

With [AiToEarn开源地址](https://github.com/yikart/AiToEarn) and [AI模型排名](https://rank.aitoearn.ai), creators can:

- Generate AI content
- Publish cross-platform
- Apply analytics for optimization
- Monetize creative output across Douyin, Kwai, WeChat, Bilibili, Rednote, YouTube, Facebook, Instagram, Pinterest, LinkedIn, Threads, and X

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## Epilogue: Creation, Emergence, and New Perspectives

At the conclusion, someone asked:  
**Was Newton’s theory of gravity invented or discovered?**

Science Captain’s reply: *“It just appeared out of nowhere.”*

This resonates with **AI emergence** — abilities materializing spontaneously once a model surpasses a parameter threshold.

Whether Newton’s breakthrough or AI’s emergent skills, **creation is often a phase shift**, not step-by-step derivation.

---

**Final Thought:**  
Perhaps the most vital AI-era question isn’t just *What can AI do for us?* but *What can AI help us understand*—  
about the universe, creation, and ultimately, ourselves.

By connecting **ancient wisdom** and **modern AI cognition**, we open doors both forward and backward in time—turning understanding itself into a shared global dialogue.

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