Partitioning of AI Models for Execution on Mixed Criticality Systems. A Workflow Approach Proposal
Résumé
We anticipate that in dependable edgeAI AI system development, only a subset of AI-inferred classes must be inferred dependably. The implication is a mixed-criticality AI execution environment where critical processing can be treated substantially differently than any non-critical processing from which is follows that the AI model must be partitioned, allowing separation of critical and non-critical AI-execution. There is currently no standard method of achieving and documenting such a state. This paper examines partitioning for mixedcriticality execution.
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