augmented

Understanding Vibe Coding in the Age of AI

Riding the Wave The software development landscape is undergoing a profound transformation, with artificial intelligence (AI) emerging as a central force shaping how software is conceived and brought to life. Among the novel trends capturing the attention of the technology community is “vibe coding,” a programming paradigm that gained significant traction in early 2025. This approach signifies a fundamental shift away from traditional manual coding practices, with AI taking on a much more active role […]

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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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aGLM

draw_conclusion(self)

ezAGI fundamental Augmented General Intelligence draw_conclusion(self) method The draw_conclusion method is designed to synthesize a logical conclusion from a set of premises, validate this conclusion, and then save the input/response sequence to a short-term memory storage. This function is a critical component in the context of easy Augmented General Intelligence (AGI) system, as it demonstrates the ability to process information, generate responses, validate outputs, and maintain a record of interactions for future reference and learning. […]

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