Feature-Orbit Attractors A Conceptual Framework for Bounded, Self-Correcting, Low-Power AI Inference Concept paper. Proposed mechanisms only. Not presented as experimentally validated. Abstract Modern AI inference is computationally expensive, memory-intensive, and increasingly energy-constrained. At the same time, many neural systems operate probabilistically and may tolerate bounded approximation, stochasticity, and noise better…
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The Issue with Mainstream Media Homogeneity * Uniform Narratives: Mainstream media outlets often appear to follow similar scripts. When viewed in isolation, this uniformity can seem natural, but a deeper analysis reveals that many reports share the same underlying narratives—potentially driven by similar data sources, corporate pressures, or political biases.…
The Problem: Unethical App Design and Its Impact * Addiction by Design: Many contemporary apps deliberately incorporate addictive features—such as infinite scroll, variable reward mechanisms, and persuasive notifications—to maximize user engagement and screen time. These strategies, while profitable, can lead to excessive usage, reduced attention spans, and overall negative…
Introduction Imagine a future where every human interacts with the digital world exclusively through their own AI agent—a personal, autonomous digital proxy. Rather than directly browsing websites or interacting with apps, users set their preferences (either explicitly or through learning algorithms), and their AI agents handle all online interactions…