Scientific Definition
Where the model runs shapes privacy, latency, cost, and capability.
Plain-English Definition
Where the model runs shapes privacy, latency, cost, and capability.
Feynman Explanation
Three different tradeoffs. Pick two.
Core Principle
Where the model runs shapes privacy, latency, cost, and capability.
Mechanisms
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Inputs (Triggers)
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Outputs (Behaviors)
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Behavioral Signature
Three different tradeoffs. Pick two.
Examples
- Mobile AI vs. data-center AI.
- Deployment architecture decision.
Pending editorial review.
Famous Experiments
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Design Principles
- Choose deliberately per use case.
Measurement Approaches
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Evidence
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The Perverse Incentive Lens™
How this behavior is exploited — and how to redesign around it.
- Choose deliberately per use case.
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Interactive Mini Network
Click any neighbor to re-center the graph and follow the threads of connection.
Knowledge Graph Neighbors
Auto-linked to the rest of the Human Behavior Taxonomy by family, domain, dimension, and shared keywords.
AI system that takes actions to achieve goals, often across tools.
Designing processes from scratch around AI capability.
The relationship between inputs and outputs changes.
How much input the model can process at once.
Underlying data distribution changes over time.
Vector representation of content for similarity and search.
Evaluation suites that no longer reflect real-world conditions.
Systematic testing of model quality, safety, and capability.
Models learning from examples in the prompt.
How much delay the user experience tolerates.
Train a smaller model to imitate a larger one.
Performance degradation as real-world data shifts.