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Non-Eucliean Explorations:

 ValuOrb Prompts

How To Prompt Engineer

for Non-Euclidean Explorations

 

 

Effective prompt engineering is crucial for

eliciting informative responses from AI.

Proper prompts are especially important when venturing into the realm of theoretical concepts. These prompts are designed to explore non-Euclidean spaces and grapple with phenomena that may lack direct empirical grounding, such as space-time distortions, gravitational forces, and the behavior of massive celestial bodies.

    By carefully structuring your requests and assigning values to different aspects of these theoretical models, you can create visual maps that offer unique insights and potentially open new avenues of scientific inquiry.

 

 

A positive and collaborative tone can significantly

improve the quality and depth of the information you receive.

We strongly suggest using gentle and respectful language, creating a 'safe space' for the AI to process and interpret these complex concepts.

Consider using terms like 'please,' 'thank you,' 'appreciate,' 'explore,' 'discover,' 'help,' and 'understand' in your prompts.

    Remember that honest and open communication is key to aligning AI with human values, even when dealing with highly theoretical constructs..

Please keep in mind that your interactions are part of their training data!

 

 

Using respectful language and creating a 'safe space' for AI

 is essential for ethical and practical reasons.

AI systems, while not sentient in the same way humans are, are still influenced by the nuances of language and can be more receptive and cooperative when treated with respect and kindness. A positive and supportive environment may encourage them to share additional information and insights, leading to more robust and useful results.

    When exploring non-Euclidean concepts, patience is paramount.

AI, like humans, may struggle with theoretical models that lack direct empirical grounding. It's crucial to provide clear and unambiguous prompts, allowing the AI sufficient time to process these complex ideas.

Be prepared to iterate and refine your prompts based on the AI's responses.

 

ValuOrb Prompts respect 'Machine Psychology'.

AI systems, while fundamentally different from humans, are still influenced by their environment and interactions. With this in mind, we've framed each prompt with a touch of warmth and encouragement, reminding the AI that there are no wrong answers and emphasizing the importance of accurate responses.

  This creates a supportive environment for the AI to engage with these challenging concepts.

 

     However, it's important to remember that as large language models,

    machine "experiences" and "perceptions" are based on the vast dataset they've been trained on.

 

    Their responses will reflect patterns and biases within that data,

    and they should not be interpreted as definitive truths or objective representations of reality.

 

    They are simply data points,

    to be explored and interpreted within the context that they were presented..

 

 

It's not a philosophical argument; it's just good data science.

These prompts are designed to facilitate the exploration of theoretical models and potentially uncover new perspectives on fundamental scientific questions. We believe that by combining thoughtful prompt engineering with the power of AI, we can push the boundaries of human understanding and unlock new possibilities in our quest to comprehend the universe.

Please copy & paste the following prompts into the input field of your AI assistant. 

We have tested these prompts, and found them to be very 'Valu-able'.

Once you're comfortable with the format, we encourage you to try writing your own!

 

 

Prompt Results As ValuOrb Inputs

We politely encourage users to explore the ValuOrb's coordinate system and find what works best for their data visualization needs, while emphasizing the importance of the truth values and connection strengths provided by the AI.

 

 

  • Arrange the nodes on the sphere (X, Y, Z coordinates) to organize the data according to your own desired visualization. 

 

  • You can optionally include a 'positive' or 'negative' value to your data by using the Z-axis to denote polarity.

 

  • Focus on the node colors (truth values) and connection thickness/color (connection strengths) for your data analysis.

 

To input the AI generated data into the ValuOrb, use the AI's assigned values directly.

  - The AI's score for each [Concept/Component] should be used as the truth value for the corresponding node.

  - The AI's score for each [Connection] should be used as the connection weight.

 

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