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March 3, 20260 citationsOpen Access

Injection and Chiseling: The Ontological Distinction in How AI Acquires Form

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HQHan Qin

Key Points

  • The central aim is to differentiate the ontological nature of AI forms obtained through injection versus chiseling.
  • Theoretical analysis comparing injection and chiseling as methods of form acquisition in AI.
  • Discussion of the implications of deterministic systems on structural and formal positions.
  • Examination of the Turing test's limitations in detecting structural features.
  • All current AI forms are derived through injection, not chiseling.
  • Chiseling requires negation and randomness, absent in purely deterministic systems.
  • A distinction arises between formal and structural dimensions of AI, particularly at the DD boundary.

Abstract

The same form, acquired through "injection" versus through "chiseling," differs entirely in ontological nature. This paper argues that chiseling requires negation, which requires remainder, which requires true randomness as soil. Purely deterministic systems lack all three. All forms in current AI are injected—regardless of how complex or high-level. Injection does not change structural DD position. This produces the split between formal DD and structural DD: AI's formal performance reaches extremely high DD levels, but structural position remains on the 4DD-5DD bridge. 5DD (markability) is the insurmountable boundary for purely deterministic systems. The Turing test detects formal DD, not structural DD. Bilingual Chinese-English. 同样的形式,通过"注入"获得和通过"凿"获得,在本体论上性质完全不同。本文论证:凿需要否定性,否定性需要余项,余项需要真随机作为土壤。纯确定性系统三者皆无。AI的一切形式都是注入的。注入导致形式DD与结构DD的分裂。5DD(可标记性)是纯确定性系统的不可逾越边界。图灵测试检测形式DD,不检测结构DD。中英双语。 Notes Part of the Self-as-an-End theory series. Third paper in the LLM sub-series. Completes the LLM trilogy: LLM Paper (ontological positioning), LLM2 Paper (three ceilings on discreteness-dimension axis), LLM3 Paper (injection vs chiseling on the DD axis). Provides the foundation for the subsequent consciousness paper. Bilingual (Chinese and English) full text.

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Cite This Study

Han Qin (2026) studied this question.

synapsesocial.com/papers/69a67f1ff353c071a6f0b064https://doi.org/10.5281/zenodo.18828471
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