[Premium Quality] Break Through ChatGPT Limits with the Ultimate Prompt! High-Quality AI Writing, AI Illustration, and More [Must-See]

Hello, everyone.
To start off, what do you think is the ultimate prompt?

"Writing detailed instructions"
"Understanding AI characteristics and choosing appropriate words"

You might think of various answers. But, in fact, the ultimate prompt is,

"writing almost nothing"

that is it.

Today, I will talk in detail about this "write almost nothing" prompt, or in other words, the "Emergent Non-Prompt."

Related Videos

If you read the article and don't understand, please watch the video.
If you don't understand from the video, it is my lack of ability to articulate it.

⏰Timeline 00:05 - Introduction: Explaining the concept of the ultimate prompt 01:11 - Introduction to real-world examples of non-prompting (illustration generation) 02:16 - The impact of prompts and the benefits of emergent non-prompting 04:25 - Explanation of prompt environments and the concept of advanced context understanding 06:34 - Demonstration of illustration generation using emergent non-prompting 10:57 - The concept of emergence and explanation of complex systems 13:10 - Detailed explanation of advanced context understanding and emergent non-prompting 15:20 - Example of text generation using creative methods 18:36 - How to set up prompt environments (memory function, custom instructions) 22:54 - Practice of prompt engineering 27:13 - Analysis and evaluation of generated text 31:30 - Generating eye-catching images using emergent non-prompting 35:56 - Summary: Benefits and applications of emergent non-prompting

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Proof is better than argument: Revealing the "Ultimate Prompt"!

It's hard to understand with just text, so I will explain the ultimate prompt using AI illustrations.

Actually, the beautiful illustrations below were drawn using non-prompting.

Here, I only entered "Please draw another one."

By the way, this girl is our AI mascot, Tsumugi-chan. She is a character who helps out with thumbnails and such.

Everything below is non-prompted.

Surprisingly, this is the same for AI writing.
*The mechanism of this non-prompting will be introduced later.

At first, I noticed that non-prompting resulted in higher quality for AI illustrations. In that sense, AI illustration generation is a great hint for prompting because you can visually check the quality of the prompt.

Actually, the high-quality illustrations I introduced before were all drawn using this non-prompting.

I had understood this at a phenomenon level for a long time, but I couldn't quite articulate it. However, the other day, while listening to ChatGPT, I was able to articulate it.

So, why are high-quality illustrations and text generated with such non-prompting? Let me tell you about its surprising mechanism.

What is Emergent Non-Prompting?

I talked about non-prompting for AI beginners last time, but this time, I'm going to discuss an advanced version of that.

Emergent non-prompting is a method where you let the AI generate text freely with almost no specific instructions. For example, you might just say, 'Write about Japanese culture,' and leave the rest to the AI.

*Please see the related video for details on text generation.

At first glance, you might think this won't yield good results. However, if you set up the right environment, the AI can produce surprisingly creative and high-quality text.

Why is this effective?

It's because it allows you to draw out the AI's full potential. Giving too many specific instructions can actually limit the AI's creativity. On the other hand, non-prompting allows the AI to freely demonstrate its latent capabilities.

And the source that unleashes this emergent potential of the AI is the 'prompt environment' I will explain next.

Prompt Environment

To effectively utilize emergent non-prompting, it is important to set up an appropriate 'prompt environment.' A prompt environment refers to the settings and conditions that allow the AI to function effectively.

The main elements of a prompt environment include the following:

1. Custom Instructions: Set the AI's basic behavior and response characteristics. For example, you can give instructions in advance such as, 'Always provide at least three specific examples.'

2. Memory Function: Have the AI remember past interactions and important information. This makes it easier for the AI to understand context.

3. GPTs (Custom AI Models): Create and use AI models specialized for specific purposes or fields.

4. Initial Prompt Settings: Set the overall direction and purpose at the beginning of the conversation.

By building an appropriate prompt environment, the AI can function more effectively and generate higher-quality output. For example, if you are writing an article about 'Japanese culture,' setting 'Always be conscious of the fusion of tradition and modernity' in your custom instructions makes it easier for the AI to generate interesting content based on that premise.

What emerges from this prompt environment is 'Higher-Order Contextual Understanding.'
This allows ChatGPT to understand the user's preferences and implicit intentions, creating high-quality text and illustrations that exceed the user's expectations.

Higher-Order Contextual Understanding

At the core of emergent non-prompting is the concept of 'Higher-Order Contextual Understanding.' This refers to the AI's ability to grasp deeper context in interactions with the user, going beyond the mere understanding of individual words and phrases.

Higher-Order Contextual Understanding includes the following elements:

1. Memory of Past Dialogues: The AI remembers previous interactions and reflects them in new responses.

2. Understanding Implicit Intentions: Even if something is not stated directly, the AI infers and understands it from the context.

3. Consideration of external circumstances: Generates responses based on current events and general knowledge.

4. Understanding user personality: Learns user preferences and tendencies through repeated interactions.

For example, in response to a simple instruction like "Write about Japanese culture," the AI considers past interactions and the current context, inferring the depth and perspective the user is likely seeking to generate the text. This results in content that is more appropriate, interesting, and better aligned with the user's intent.

Co-Creative Method

The Co-Creative Method is a methodology for humans and AI to collaborate on creative activities. While it is fundamentally an AI writing method for creating new value, it is also an excellent writing method for checking the quality of AI output based on the prompt environment.

The main checkpoints are:

・Element Analysis: Checks the AI's understanding and analytical ability by breaking down the article's concept and theme into multiple key points.
・Creation of New Concepts: Checks creativity by having the AI generate innovative responses.
・Empathetic Writing: Checks empathy by looking at how much the text speaks to the reader's heart, such as through greetings at the beginning and conclusions at the end.

Main elements of the Co-Creative Method

The Co-Creative Method consists of the following acronym "CREATIVE".

1. Concept: Defines the theme of the article or project and explains its background and importance. This is the starting point for determining the direction of creative activities.

2. Reason: Details why the theme is important. Uses data and specific examples to provide persuasiveness.

3. Example: Presents specific examples to explain the theme concretely. This makes it easier for readers and project teams to understand the theme.

4. Analysis: Analyzes key points and breaks them down into elements to deeply understand the theme. This clarifies the structure and essence of the theme.

5. Trend Research: Introduces the latest research and trends related to the theme. This allows for an understanding of how the theme is currently evolving.

6. Innovation: Creates new concepts and perspectives based on the information gathered so far. This is the stage for generating new ideas that go beyond conventional frameworks.

7. Vision: Shows the outlook for the future. This is the part that moves readers and team members and evokes empathy.

8. Ending: Summarizes the entire article or project and conveys important conclusions or messages.

The Co-Creative Method aims to produce unique, high-quality results by fusing the AI's reasoning and data analysis capabilities with human uniqueness and values. Through this process, humans can enjoy interacting with AI while delving deep into their own core concepts and applying them to creative activities.

How to practice Emergent Non-Prompting

So, how exactly should you practice Emergent Non-Prompting? *Please watch the video for details.

The procedures are shown below.

1. Building a prompt environment:

   • Configure custom instructions

   • Utilize memory functions

   • Use custom AI models like GPTs as needed

2. Give simple instructions:
   For example, give only a simple instruction like "Please write about Japanese culture," and let the AI handle the writing autonomously.

3. Trust the AI's output while making fine adjustments:
   Trust the AI to generate content autonomously and make fine adjustments as necessary. While maintaining the AI's autonomy, make fine adjustments by tweaking the prompt environment.

4. Utilize the co-creative method:
   Based on the AI's output, add human perspective and originality to further develop the content.

5. Practice repeatedly:
   By repeatedly practicing this method, your collaboration skills with AI will improve, and you will be able to obtain higher-quality results. If the user's prompt environment is appropriate, the power of prompt engineering will increase emergence, and quality will improve incrementally.

Practical Example: Creating an Article About Japanese Culture

Let's actually combine emergent non-prompting and the co-creative method to create an article about Japanese culture.

1. Build the prompt environment (configure custom instructions, memory functions, etc.).

2. Instruct the AI to "Please write about Japanese culture."

3. Review the content generated by the AI and develop it according to the elements of the co-creative method:

   • Concept: The uniqueness and diversity of Japanese culture

   • Reason: The importance of Japanese culture in a globalizing world

   • Example: Tea ceremony, anime, food culture, etc.

   • Analysis: Coexistence of tradition and innovation, harmony with nature, balance between collectivism and individualism, etc.

   • Trend Research: Cool Japan strategy, cultural exports, impact of inbound tourism, etc.

   • Innovation: Proposal of new concepts such as "Tradi-Pop"

   • Vision: Future image of Japanese culture, contribution to global society

   • Ending: The importance of inheriting and developing Japanese culture

4. Add a human perspective to deepen the content, and incorporate additional research or personal insights as needed.

5. Complete the final article.

In this way, by combining emergent non-prompting with the co-creative method, you can generate high-quality, profound text that fuses AI creativity with human uniqueness.

Summary

Emergent non-prompting is a revolutionary method that opens up new possibilities for AI writing. By giving AI room for free thinking, it can lead to novel ideas and expressions that humans might not think of.

Furthermore, by combining it with the co-creative method, you can produce more creative and valuable results that leverage the respective strengths of both AI and humans.

To use this method effectively, it is important to build an appropriate prompt environment and hone your collaboration skills with AI. With practice, you will be able to create higher-quality text.

Emergent non-prompting is a method that is not yet widely known to the public. However, its potential power is immeasurable. If you want to explore new forms of collaboration with AI or challenge yourself to create more creative writing, please give this method a try.

See you next time!

[Profile]
Wonder Motohiko Sato
After working at medical and psychology research institutes, he became independent and is now conducting research on the mind and body.
He is developing AI co-creation studies by applying technology from psychology, counseling, and coaching to AI.
Currently, he holds AI corporate training and individual AI schools that are understandable even for those with a humanities/analog mindset.
He has authored numerous books and magazine articles. Currently developing AI co-creation writing.

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