User Tools

Site Tools


ai_intuition

Differences

This shows you the differences between two versions of the page.

Link to this comparison view

Both sides previous revisionPrevious revision
Next revision
Previous revision
ai_intuition [2025/05/27 23:36] – [Class Overview] eagleeyenebulaai_intuition [2025/05/27 23:51] (current) – [Best Practices] eagleeyenebula
Line 69: Line 69:
  
 1. **Analyze Input Data**:   1. **Analyze Input Data**:  
-   Feed fragmented, ambiguous, or incomplete data to `sense_pattern()` for intuitive feedback.+   Feed fragmented, ambiguous, or incomplete data to `sense_pattern()` for intuitive feedback.
  
 2. **Generate Interpretive Insights**:   2. **Generate Interpretive Insights**:  
-   Receive subjective and non-deterministic insights into the potential meaning of the data.+   Receive subjective and non-deterministic insights into the potential meaning of the data.
  
 3. **Customize for Use Cases**:   3. **Customize for Use Cases**:  
-   Extend the randomness or integrate structured interpretations into specific applications, such as storytelling or exploratory data analysis. +   Extend the randomness or integrate structured interpretations into specific applications, such as storytelling or exploratory data analysis.
- +
---- +
 ===== Usage Examples ===== ===== Usage Examples =====
  
 Here are examples that demonstrate how to practically and creatively use the **Intuition** class, along with extensions for more advanced functionality. Here are examples that demonstrate how to practically and creatively use the **Intuition** class, along with extensions for more advanced functionality.
- 
---- 
- 
 ==== Example 1: Basic Intuition Implementation ==== ==== Example 1: Basic Intuition Implementation ====
  
 This example showcases basic usage of the `sense_pattern()` method for interpreting a fragment of data. This example showcases basic usage of the `sense_pattern()` method for interpreting a fragment of data.
  
-```python+<code> 
 +python
 from ai_intuition import Intuition from ai_intuition import Intuition
- +</code> 
-Initialize the Intuition system+**Initialize the Intuition system** 
 +<code>
 intuitive = Intuition() intuitive = Intuition()
- +</code> 
-Feed input data+**Feed input data** 
 +<code>
 input_data = ["0, 1, 1, 2, 3" # A fragment of the Fibonacci sequence input_data = ["0, 1, 1, 2, 3" # A fragment of the Fibonacci sequence
 result = intuitive.sense_pattern(input_data) result = intuitive.sense_pattern(input_data)
- 
 print(result) print(result)
  
 # Output (example): # Output (example):
 # Intuition says: This pattern hints at beauty. # Intuition says: This pattern hints at beauty.
-``` +</code>
 **Explanation**:   **Explanation**:  
-The method interprets the Fibonacci sequence as hinting at either *beauty*, *chaos*, or *connection*, depending on the randomized result. +   The method interprets the Fibonacci sequence as hinting at either **beauty**, **chaos**, or **connection**, depending on the randomized result.
- +
---- +
 ==== Example 2: Interpreting Empty Input ==== ==== Example 2: Interpreting Empty Input ====
  
 Intuition derives meaning even in the absence of data. Intuition derives meaning even in the absence of data.
  
-```python +<code> 
-Initialize the Intuition system+python 
 +</code> 
 +**Initialize the Intuition system** 
 +<code>
 intuitive = Intuition() intuitive = Intuition()
- +</code> 
-Pass no input data+**Pass no input data** 
 +<code>
 result = intuitive.sense_pattern([]) result = intuitive.sense_pattern([])
  
Line 125: Line 121:
 # Output: # Output:
 # From the silence, a possibility emerges: Something unseen is forming. # From the silence, a possibility emerges: Something unseen is forming.
-```+</code>
  
 **Explanation**:   **Explanation**:  
-When no input data is provided, the `Intuition` system interprets possibility instead of returning an error or null response. +   When no input data is provided, the `Intuition` system interprets possibility instead of returning an error or null response.
- +
---- +
 ==== Example 3: Probability-Based Insights ==== ==== Example 3: Probability-Based Insights ====
  
 Using weighted randomness to generate more meaningful results. Using weighted randomness to generate more meaningful results.
  
-```python+<code> 
 +python
 import random import random
  
Line 154: Line 148:
         hint = random.choices(choices, weights=weights)[0]         hint = random.choices(choices, weights=weights)[0]
         return f"Intuition says: This pattern hints at {hint}."         return f"Intuition says: This pattern hints at {hint}."
 +</code>
  
- +**Usage** 
-Usage+<code>
 intuitive = ProbabilisticIntuition() intuitive = ProbabilisticIntuition()
 result = intuitive.sense_pattern(["fractals", "steady growth"]) result = intuitive.sense_pattern(["fractals", "steady growth"])
Line 163: Line 158:
 # Output: # Output:
 # Intuition says: This pattern hints at beauty.  (Most likely due to weighting) # Intuition says: This pattern hints at beauty.  (Most likely due to weighting)
-```+</code>
  
 **Explanation**: **Explanation**:
-Adjust weights for randomness to favor specific outputs, tailoring the output for specific contexts or applications. +   Adjust weights for randomness to favor specific outputs, tailoring the output for specific contexts or applications.
- +
---- +
 ==== Example 4: Intuition with Pattern Recognition ==== ==== Example 4: Intuition with Pattern Recognition ====
  
 Integrate a pattern recognition mechanism to supplement intuition with logic. Integrate a pattern recognition mechanism to supplement intuition with logic.
  
-```python+<code> 
 +python
 import re import re
  
Line 189: Line 182:
         return super().sense_pattern(input_data)         return super().sense_pattern(input_data)
  
- +</code> 
-Usage+**Usage** 
 +<code>
 intuitive = LogicEnhancedIntuition() intuitive = LogicEnhancedIntuition()
 result = intuitive.sense_pattern(["0, 1, 1, 2, 3"]) result = intuitive.sense_pattern(["0, 1, 1, 2, 3"])
Line 197: Line 191:
 # Output: # Output:
 # Intuition says: This pattern resembles Fibonacci—a balanced progression of growth. # Intuition says: This pattern resembles Fibonacci—a balanced progression of growth.
-```+</code>
  
 **Explanation**: **Explanation**:
-Enhances intuition by detecting recognized patterns (e.g., Fibonacci sequences), combining logic with intuitive abstraction. +   Enhances intuition by detecting recognized patterns (e.g., Fibonacci sequences), combining logic with intuitive abstraction.
- +
----+
  
 ==== Example 5: Persistent Intuition Logs ==== ==== Example 5: Persistent Intuition Logs ====
Line 208: Line 200:
 Save intuitive insights for future recall or analysis. Save intuitive insights for future recall or analysis.
  
-```python+<code> 
 +python
 import datetime import datetime
  
Line 232: Line 225:
         return self.memory         return self.memory
  
- +</code> 
-Usage+**Usage** 
 +<code>
 intuitive = PersistentIntuition() intuitive = PersistentIntuition()
 print(intuitive.sense_pattern(["0, 1, 1, 2, 3"])) print(intuitive.sense_pattern(["0, 1, 1, 2, 3"]))
Line 240: Line 234:
 for memory in intuitive.get_memory_log(): for memory in intuitive.get_memory_log():
     print(memory)     print(memory)
-```+</code>
  
 **Explanation**: **Explanation**:
-Stores intuitive outputs along with corresponding input and timestamps. +   Stores intuitive outputs along with corresponding input and timestamps. 
-Enables applications that require intuition-based decision logs for review or learning. +   * Enables applications that require intuition-based decision logs for review or learning.
- +
---- +
 ===== Use Cases ===== ===== Use Cases =====
  
 1. **Creative Writing and Storytelling**:   1. **Creative Writing and Storytelling**:  
-   Generate abstract insights to inspire narratives or characterize AI with "emotions" or "intuition."+   Generate abstract insights to inspire narratives or characterize AI with "emotions" or "intuition."
  
 2. **Philosophical Simulations**:   2. **Philosophical Simulations**:  
-   Use intuition to mimic human abstract thought processes, introducing unexpected perspectives.+   Use intuition to mimic human abstract thought processes, introducing unexpected perspectives.
  
 3. **Exploratory Data Analysis**:   3. **Exploratory Data Analysis**:  
-   Analyze fragmented data to gather creative insights or hypotheses for further investigation.+   Analyze fragmented data to gather creative insights or hypotheses for further investigation.
  
 4. **Layered Decision-Making**:   4. **Layered Decision-Making**:  
-   Integrate into AI systems requiring both logical and intuitive responses in decision processes.+   Integrate into AI systems requiring both logical and intuitive responses in decision processes.
  
 5. **Persistent Historical Analysis**:   5. **Persistent Historical Analysis**:  
-   Save and analyze intuitive responses as part of a growing AI "memory." +   Save and analyze intuitive responses as part of a growing AI "memory."
- +
---- +
 ===== Best Practices ===== ===== Best Practices =====
  
 1. **Embrace Randomness in Creativity**:   1. **Embrace Randomness in Creativity**:  
-   Allow intuitive randomness to inspire creativity in storytelling or philosophical simulations.+   Allow intuitive randomness to inspire creativity in storytelling or philosophical simulations.
  
 2. **Balance Logic with Intuition**:   2. **Balance Logic with Intuition**:  
-   Where appropriate, build logic-based extensions for enhancing intuitive outputs.+   Where appropriate, build logic-based extensions for enhancing intuitive outputs.
  
 3. **Add Context Sensitivity**:   3. **Add Context Sensitivity**:  
-   Extend intuition to respond differently based on thematic or contextual requirements.+   Extend intuition to respond differently based on thematic or contextual requirements.
  
 4. **Log and Analyze Outputs**:   4. **Log and Analyze Outputs**:  
-   Persist intuitive insights for auditing, reflection, or interactive narrative systems.+   Persist intuitive insights for auditing, reflection, or interactive narrative systems.
  
 5. **Extend with Weighted Outputs**:   5. **Extend with Weighted Outputs**:  
-   Use probability or bias to increase the meaningfulness of randomness for practical applications. +   Use probability or bias to increase the meaningfulness of randomness for practical applications.
- +
---- +
 ===== Conclusion ===== ===== Conclusion =====
  
ai_intuition.1748389006.txt.gz · Last modified: 2025/05/27 23:36 by eagleeyenebula