RAGE

RAGE

RAGE Retrieval Augmented Generative Engine

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aGLM with enhanced RAGE from MASTERMIND

aGLM, or Autonomous General Learning Model, is a sophisticated machine learning model that integrates aspects of both supervised and unsupervised learning to analyze and interpret data across various applications like natural language processing, image recognition, and financial forecasting. This model is designed to efficiently handle large volumes of data and is particularly effective as a foundational tool for building more complex models. Key features of aGLM include: Dynamic Learning: aGLM can process and learn from […]

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GraphRAG Evolves:

Understanding PathRAG and the Future of the Retrieval Augmented Generation Engine Retrieval Augmented Generative Engine (RAGE) has enhanced how we interact with large language models (LLMs). Instead of relying solely on the knowledge baked into the model during training, RAG systems can pull in relevant information from external sources, making them more accurate, up-to-date, and trustworthy. But traditional RAG, often relying on vector databases, has limitations. A new approach, leveraging knowledge graphs, is rapidly evolving, and […]

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fundamental AGI

putting the fun into a fundamental augmented general intelligence framework as funAGI funAGI is a development branch of easyAGI. easyAGI was not being easy and SimpleMind neural network was proving to not be simple. For that reason is was necessary to remove reasoning.py and take easyAGI back to its roots of BDI Socratic Reasoning from belief, desire and intention. So this back to basics release should be taken as a verbose logging audit of SocraticReasoning […]

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