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  • Landscape Reading Model — Text Network Representation

    How do we perceive a text when we read it? The answer to this question can help us understand how attention functions and identify various strategies to enhance our writing. Additionally, it can inspire new methods of reading that increase engagement and accessibility. In this article, we’re going to demonstrate how the landscape reading model can be represented using text networks and how this representation helps generate new ideas and insights in InfraNodus.

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  • HRV Analysis for Peak Athletic Performance: DFA vs LF/HF

    Heart rate variability (HRV) is a powerful window into the autonomic nervous system, helping athletes and coaches peek into the balance between the calming parasympathetic and the activating sympathetic drives. Advanced techniques like detrended fluctuation analysis (DFA) of HRV are bringing fractal and non-linear dynamics into the mix, offering a deeper understanding of how our nervous system regulates exercise intensity and responds to training stress.

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  • Graph RAG and LLMs: How Knowledge Graphs Can Improve AI Ideation

    How to use knowledge graphs to improve the responses of LLM and your own thinking.

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  • Setting Up DeepSeek on a Local or Private Server: A Step-by-Step Tutorial

    How to ensure that your DeepSeek model is running locally and not sending your data anywhere. A full step-by-step non-technical installation guide.

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  • Mind Map AI Generator

    In this article, we will present an AI mind map generator — InfraNodus — that can create a knowledge graph from any text. Unlike other tools, it doesn’t start from a central idea, because that’s not how our mind works. Rather, it maps out all the ideas present within a text as a network graph, so the resulting mind map will be more rhizomatic, helping you see the patterns rather than presenting hierarchies (which often do not even exist).

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