AI Token Ecology Core Concepts
Within the theoretical framework of contemporary generative artificial intelligence, Token Ecology provides a perspective that transcends linear language models, viewing tokens as constituting a multi-layered, multi-species associative ecosystem within AI language models. In Token Ecology, tokens do not exist in isolation, but rather within AI language models, tokens (word units, symbolic units) are generated, transmitted, interact, and evolve in an ecosystem-dynamic manner, forming multi-layered symbiotic or parasitic structures with human language, corpora, social culture, and platform media as a holistic view.
Three core metaphors as the theoretical foundation :
- Infopiphytism: Information Epiphytic Metaphor
- Infoparasitism: Information Parasitic Metaphor
- Infosymbiosis: Information Symbiotic Metaphor
人工智慧符號生態學核心概念
在當代生成式人工智慧的理論框架中，Token Ecology（符號生態學） 提供一種超越線性語言模型的視角，將 tokens 視作在 AI 語言模型內部構成一個多層次、多物種關聯的生態系統。Token Ecology中 Token 並非孤立存在，是在 AI 語言模型內部，tokens（詞元、符號單位）以生態系統動態的方式被生成、傳遞、互動、演化，並與人類語言、語料、社會文化、平台媒介形成多層次共生或寄生結構的整體觀。
三種核心隱喻的理論基礎：
- Infopiphytism: 資訊附生隱喻 (Epiphytic Metaphor)
- Infoparasitism: 資訊寄生隱喻 (Parasitic Metaphor)
- Infosymbiosis: 資訊共生隱喻 (Symbiotic Metaphor)
續篇
- Reconstructing “Token” the Fifth Dimension as an “Information-Relational Manifold" — AI Unified Field Theory “Token”第五維度重構為「信息—關聯流形」— AI 統一場論
- “Token" as the Fifth Dimension: From Physical to Informational Dimensional Expansion “Token" 作為第五維度 – 從物理到資訊維度的擴張
- Semantics and Meaning in Language Models LLM語言模型的「語義結構」 與「語意傾向」
- LLM 神經網路裡的疊加 (Superposition) ：量子電腦發展的可能性
- LLM as Language Sieve: An Information Intelligence Generation Mechanism Based on Small World Networks “大型語言模型（LLM）作為語言篩"
Reconstructing “Token” the Fifth Dimension as an “Information-Relational Manifold" — AI Unified Field Theory “Token”第五維度重構為「信息—關聯流形」— AI 統一場論
“AI serves not as a substitute for human intellect…
“Token" as the Fifth Dimension: From Physical to Informational Dimensional Expansion “Token" 作為第五維度 – 從物理到資訊維度的擴張
Abstract This paper argues that the token vector space …
Semantics and Meaning in Language Models LLM語言模型的「語義結構」 與「語意傾向」
Example I: Shadow When we mention “shadow," s…
LLM 神經網路裡的疊加 (Superposition) ：量子電腦發展的可能性
前言： 在經典的物理學或量子力學中，疊加是指一個系統可以同時處於多個狀態的組合。例如，一個波可以同時是多個不同…
LLM as Language Sieve: An Information Intelligence Generation Mechanism Based on Small World Networks “大型語言模型（LLM）作為語言篩"
LLM as Language Sieve: An Information Intelligence Gene…
Sieve and Intelligence: LLMs as Extractors of Metaphorical Entity Information Embedded in Data for Intelligence Generation 篩與智 : LLM 作為提取存於資料中隱喻實體資訊以生成智能
Sieve and Intelligence: LLMs as Extractors of Meta…
AI Token Ecology Core Concepts 人工智慧符號生態學核心概念
AI Token Ecology 1. Introduction Within the th…
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Information Parasitism and Architectural Ecosystems: A …
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Preface A groundbreaking study published by OpenAI in J…
III. 資訊寄生與「物以類聚」：數位時代的認知探索Information Parasitism and “Birds of a Feather": Cognitive Exploration in the Digital Age
Abstract This paper takes “birds of a feather floc…
II. 資訊寄生：符號學視角下的AI大語言模型可解釋性研究 Information Parasitism: A Semiotic Analysis of AI Large Language Model Interpretability
Abstract This paper centers on the concept of “inf…
I. 資訊寄生 InfoParasitism
I. Introduction: The Revelation of Information Parasiti…
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