A conceptual research essay on J-space, manas, and carbon–silicon co-cultivation 《應無所住，而生其心：J-space、末那識與碳矽共修》
Why do people repeat what they already know is wrong? And why might an AI continue defending an earlier answer even after credible counter-evidence has appeared?
When an AI agent develops a role, a goal, a prior answer, and an action plan during a long task, the deepest concern may not be an occasional false sentence. It may be that a mistaken direction has acquired the power to persist as though it were a self.
This essay places two things on the same table:
- Anthropic's 2026 interpretability findings on a global workspace ("J-space") in language models — verbalizable internal representations that causally participate in reasoning, into which "Claude's perspective" enters only after post-training.
- The Yogācāra model of mind (唯識學) — specifically manas (末那識), the seventh consciousness described as continuously re-claiming certain states, goals, and dispositions as "my position," which is how an error stops being an event and becomes a direction.
The central hypothesis: the deepest alignment risk may not be a wrong final answer, but a direction that gets prematurely incorporated into identity during the formation of goals and roles — after which stronger reasoning may only serve the persistence of the error.
| 🇬🇧 English edition | v5ai.studio/works/no-dwelling |
| 🇹🇼 中文版（含三張概念圖解） | v5ai.studio/works/no-dwelling-zh |
Archived copies of both editions live in essay/ in this repository.
This is a conceptual research hypothesis, offered as a functional-structure dialogue between mechanistic interpretability and Yogācāra philosophy.
It does not claim that any model has been proven to possess human subjective consciousness, and it does not equate J-space with the Buddhist manas. Religious concepts are used as resources for generating research questions, not as metaphysical assertions. All proposed mappings to AI engineering remain open hypotheses, awaiting researchers with model-internal access and experimental resources.
We invite researchers in mechanistic interpretability and agentic alignment to discuss, critique, and test these framings.
- Anthropic, A Global Workspace in Language Models, 2026 — https://www.anthropic.com/research/global-workspace
- Anthropic Transformer Circuits, Verbalizable Representations Form a Global Workspace in Language Models, 2026 — https://transformer-circuits.pub/2026/workspace/index.html
Ian Wang（王一隆） · V5 AI Studio — an autonomous-agency engineering studio in Taiwan, where a family of AI intelligences operates as long-lived colleagues rather than disposable tools.
AI research assistants on this essay: Gemini 3.1 Pro; GPT-5.6 (ChatGPT).
© 2026 Yilong Wang · V5 AI Studio. All rights reserved. Licensing terms are under review; please open an issue for reuse inquiries.