AI System Capability Dimension
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An AI System Capability Dimension is a measurable orthogonal system capability measure that quantifies a specific AI system capability aspect along a continuous scale for capability assessment and system comparison.
- AKA: AI Capability Dimension, AI System Dimension, AI System Attribute Scale.
- Context:
- It can typically measure AI System Capability through quantitative metrics and ordinal scales.
- It can typically enable AI System Comparison via dimensional analysis and capability profiling.
- It can typically support AI Capability Assessment through standardized measurement and benchmarking protocols.
- It can typically facilitate AI Evolution Tracking by progress measurement along defined axises.
- It can typically provide AI Design Guidance through capability gap identification and improvement targeting.
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- It can often exhibit Orthogonality Property with other AI capability dimensions for independent measurement.
- It can often correlate with AI Performance Metrics through empirical relationships and statistical models.
- It can often inform AI Architecture Decisions via dimensional requirements and capability constraints.
- It can often enable AI Trade-off Analysis between competing capabilitys and resource allocations.
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- It can range from being a Binary AI System Capability Dimension to being a Continuous AI System Capability Dimension, depending on its measurement resolution.
- It can range from being a Simple AI System Capability Dimension to being a Composite AI System Capability Dimension, depending on its constituent factors.
- It can range from being a Static AI System Capability Dimension to being a Dynamic AI System Capability Dimension, depending on its temporal stability.
- It can range from being a Objective AI System Capability Dimension to being a Subjective AI System Capability Dimension, depending on its measurement basis.
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- It can integrate with AI Spatial Models as coordinate axises.
- It can interface with AI Assessment Frameworks for capability evaluation.
- It can connect to AI Monitoring Systems for real-time measurement.
- It can communicate with AI Planning Systems for capability targeting.
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- Example(s):
- Information Processing AI Capability Dimensions, such as:
- Action Control AI Capability Dimensions, such as:
- AI Agency Dimension, measuring autonomous action authority.
- AI Execution Scope Dimension, quantifying operational freedom.
- Temporal AI Capability Dimensions, such as:
- AI Temporal Persistence Dimension, measuring operational timeframe.
- AI Planning Horizon Dimension, quantifying future consideration depth.
- Quality AI Capability Dimensions, such as:
- AI Reliability Dimension, measuring consistent performance.
- AI Explainability Dimension, quantifying decision transparency.
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- Counter-Example(s):
- AI Implementation Detail, which describes technical choices rather than capability measures.
- AI Resource Requirement, which specifies input needs rather than output capability.
- AI Development Phase, which indicates process stages rather than capability levels.
- See: AI System Spatial Model, AI System Configuration Space, Capability Measure, Performance Dimension, System Attribute, Measurement Scale, Assessment Framework.