AI·rete·RAG
An open-source architectural project combining the Rete rule engine with Retrieval-Augmented Generation (RAG) technology. It uses the rule engine for deterministic decision-making and RAG for generating natural-language explanations, addressing auditability and interpretability challenges in AI system decision-making.
Timeline (last 90 days)
AI·rete·RAG is an open-source project that uses the Rete rules engine for deterministic decision-making and RAG to explain the reasoning behind decisions.
AI·rete·RAG does not involve deep integration at the model level, but instead divides responsibilities at the application architecture level, representing a loosely coupled neuro-symbolic practice.
Having a large model both make decisions and provide reasoning carries a risk: the reasoning the model provides may be a post-hoc rationalization of an already generated conclusion rather than the true basis for the decision.
In loosely coupled architectures such as AI·rete·RAG, the interface design for converting rule trigger signals into RAG queries becomes a key bottleneck for system robustness.
All Facts (4)
AI·rete·RAG is an open-source project that uses the Rete rules engine for deterministic decision-making and RAG to explain the reasoning behind decisions.
50%UnverifiedAI·rete·RAG does not involve deep integration at the model level, but instead divides responsibilities at the application architecture level, representing a loosely coupled neuro-symbolic practice.
50%UnverifiedHaving a large model both make decisions and provide reasoning carries a risk: the reasoning the model provides may be a post-hoc rationalization of an already generated conclusion rather than the true basis for the decision.
50%UnverifiedIn loosely coupled architectures such as AI·rete·RAG, the interface design for converting rule trigger signals into RAG queries becomes a key bottleneck for system robustness.
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