AGI Pipedream

AGI Pipedream

Why Optimization Cannot Produce Persons

Preface

  • Scope and intent

  • What this document is not claiming

  • The category error it addresses

Part I — The Core Misunderstanding

1. The AGI Pipedream

  • AGI as a projection error

  • Why scaling success masquerades as ontological progress

  • The confusion between capability and kind

2. Optimization Is Not Emergence

  • Closed representational spaces vs open evolutionary spaces

  • Why no dataset can substitute for an environment

  • Loss functions as anti-creative constraints

3. Why “Adding Components” Fails

  • Goals, memory, tools, embodiment

  • Why augmentation preserves identity instead of transforming it

  • The impossibility of modular personhood

Part II — Semantic Clouds

4. What a Semantic Cloud Is (Formal Definition)

  • Latent manifolds as compressed human artifacts

  • Semantic distance vs physical constraint

  • Reversibility as a defining property

5. Why LLMs Are the Ultimate Semantic Compressors

  • Compression–reasoning equivalence

  • Why this is a strength, not a failure

  • The end of token-centric thinking

6. Time and Space as Non-Native Variables

  • Ordering vs dynamics

  • Embedding geometry vs locality

  • Why time and space appear only as content

Part III — The Reasoning Fallacy

7. Why “LLM Reasoning Failures” Are Category Errors

  • Reasoning as invariant preservation

  • Why LLMs never enter the regime where reasoning exists

  • Semantic navigation vs logical inference

8. Why Constraint Injection Changes the Problem

  • Kepler → Newton papers as regime shifts

  • Numerical dynamical modeling vs language modeling

  • Why success there does not transfer back

Part IV — Being vs Having a World Model

9. Organisms as World Models

  • Structure as hypothesis

  • Irreversible coupling to environment

  • Survival as truth signal

10. World Models Before Language

  • Pre-linguistic cognition

  • Language as externalized model sharing

  • Civilization as incarnated meta-model

11. Why LLMs Can Only Have Models, Not Be Them

  • Dependence on lineage artifacts

  • No endogenous stakes

  • No identity constituted by consequence

Part V — The Human Parallel

12. When Humans Become LLM-like

  • Over-reliance on linguistic and technological exo-models

  • Delamination from embodied cognition

  • Social loss functions replacing reality feedback

13. Education, Signaling, and Constraint Navigation

  • Why schooling often changes access, not capability

  • Institutional boundaries vs human capital

  • Phase delays, not productivity gains

Part VI — The Transhuman Fork

14. Why Robotic Embodiment Does Not Solve the Problem

  • Mechanical reproduction vs biological lineage

  • Mass production vs variance and selection

  • Why sensors do not create stakes

15. Synthetic Persons (What Would Actually Be Required)

  • Growth from scratch

  • Self-reproduction with variance

  • Selection under real consequence

  • Continuous multi-scale self-relation

Part VII — The Real Choice

16. Two Futures

  • Synthetic emergence preserving meaning

  • Mechanistic displacement via p-zombies

  • Why there is no middle ground

17. Why LLMs Cannot Become What We Are

  • Identity-preserving transformations

  • Why becoming requires ceasing to be

  • The hard boundary no roadmap crosses

Conclusion — No Failure, Only Misapplied Questions

  • LLMs as wheels mistaken for carts

  • The Zen moment: stopping the wrong search

  • Using semantic engines for what they are

Appendices

A. Formal Constraints Required for Personhood

B. Mathematical Notes on Reversibility and Irreversibility

C. Why “Agentic LLMs” Fail Under Adversarial Analysis

D. Glossary (Semantic Cloud, World Model, Constraint, Irreversibility)

Final compression (optional subtitle)

LLMs are complete.
What they are complete for is not becoming us. 

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