The theory that all knowledge is mediated by signs—that we never access reality directly but always through representations: language, images, symbols, concepts. There is no unmediated knowing, no raw contact with the real. Epistemological Semiotics studies how sign systems shape what can be known, how representation enables and constrains understanding. It's the recognition that we are always, already in the realm of meaning, and that meaning-making is the condition of knowledge, not its obstacle.
"You think you're experiencing reality directly? Epistemological Semiotics says: you're experiencing reality filtered through language, culture, personal history—all sign systems. There's no escape into the raw real. The signs are the only access you have. Learn to read them or stay confused."
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A neural architecture that performs semantic compression using nuclear diversity preservation, operating in pure vector space to bypass linguistic tokenization while maintaining conceptual understanding. The system compresses high-dimensional embeddings (e.g., 384D → 256D) through a teacher-student knowledge distillation framework that employs extreme weighting to prevent mode collapse, creating mathematical "semantic GPS coordinates" where related concepts cluster in measurable dimensional neighborhoods.
The Latent Neurolese Semantic Encoder achieved 6x inference speedup and 35% memory reduction while maintaining 63.5% semantic preservation through its nuclear diversity training methodology, demonstrating that AI systems can reason directly with compressed mathematical concepts rather than linguistic tokens.
by Trentism July 9, 2025
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