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fundamental augmented general intelligence

funAGI workflow fundamental autonomous general intelligence framework

The funAGI system is designed as a modular framework for developing an autonomous general intelligence. The workflow integrates several components and libraries to achieve adaptability, dynamic interaction, continuous optimization, and secure data management. Below is a detailed explanation of the funAGI workflow based on the provided files and documentation. 1. Component Initialization 2. Core AGI Logic 3. User Interaction 4. Reasoning and Logic 5. API and Integration 6. Communication and Interaction 7. Installation and Requirements […]

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mindX as a protocol — multi-stream inference, mindX in parallel

Querying many providers at once and reconciling their answers turns latency and single-model risk into parallel, consensus-checked throughput.

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AGInt: the cognitive engine at the heart of mindX — Perception, Orientation, Decision, Action, with RAGE for memory

AGInt: the cognitive engine at the heart of mindX — Perception, Orientation, Decision, Action, with RAGE for memory

Why /core matters, how the P-O-D-A loop connects beliefs to behavior, and the four-tier RAGE memory cascade (STM → LTM → pgvector → IPFS) that keeps the deliberation layer grounded.

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