Detecting Patterns: The Basics
-
Simple Pattern Detection:
- Consider the sequence:
ABCABC
. - The distance between
A
andB
is one character. - The distance between
B
andA
is two characters. -
Key Point:
AB
is a stronger pattern because it occurs with less distance between the values thanBA
.
- Consider the sequence:
-
Pursuer and Evader Points:
- Each character has a pursuer point and an evader point.
- Pursuer points move towards the evader points of characters that precede them.
- Evader points move away from the pursuer points of characters that precede them.
-
In the sequence
ABCABC
:- B's pursuer point moves strongly towards A's evader point because they are one character apart.
- A's evader point moves more weakly away from B's pursuer point because they are two characters apart.
Key Insight: B's pursuer point is chasing A's evader point more strongly than A's evader point is escaping, leading to their co-location. This co-location indicates a strong pattern based on frequency and proximity.
Principles for Advanced AI
-
Real-Time Data Processing:
- Machine learning should operate on data in real time, enabling immediate responses to new information.
-
Parallelization:
- Every character, byte, or primitive value fed through the AI should, in principle, be able to be processed fully in parallel to every other piece of information.
-
Running Calculations:
- Values critical to decision-making should be computed continuously, on the fly, to support real-time processing.
-
Threshold-Based Decisions:
- Use thresholds to make decisions quickly and efficiently. If a choice hinges on whether something exceeds or doesn't exceed a threshold, the decision can be made rapidly, which is crucial for real-time operation.
Conclusion:
- By applying these principles alongside the basics of pattern detection, we can develop AI that operates effectively and powerfully in real-time environments.
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