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aGLM

aGLM, or Autonomous General Learning Model, is designed to operate as a core model for autonomous data parsing and learning from memory in the context of artificial intelligence systems. It’s a pivotal element within a broader system called RAGE (Retrieval Augmented Generative Engine). Key aspects and functionalities of aGLM: Autonomous Learning: aGLM is built to learn autonomously from interactions and data retrievals. It continuously updates its knowledge base, refining its capabilities based on new data […]

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RAGE MASTERMIND with aGLM

RAGE MASTERMIND with aGLM: A Comprehensive Analysis In the rapidly evolving field of artificial intelligence and machine learning, the integration of advanced generative models with autonomous systems has become a focal point for developers and researchers. One such integration is the RAGE MASTERMIND with aGLM (Autonomous General Learning Model), a pioneering approach in AI development. This report delves into the specifics of this integration, exploring its components, functionalities, and potential implications in the broader context […]

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together ai

aGLM MASTERMIND RAGE Mixtral8x7B playground 1

together.ai provides a cloud environment playground for a number of LLM including Mixtral8x7Bv1. This model was chosen for the 32k ++ context window and suitable point of departure dataset for deployment of aGLM Autonomous General Learning Model. aGLM design goals include RAGE with MASTERMIND controller for logic and reasoning. The following three screenshots show the first use of aGLM recognising aGLM and MASTERMIND RAGE components to include machine.dreaming and knowledge as THOT from aGLM parse. […]

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