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Grounding World Models

From Topological Closure to Open Manifold Architecture.
A framework for verified intelligence based on thermodynamic necessity.

Grounding JEPA for Active Manifold Intelligence: from topological closure to open manifold architecture
Grounding JEPA table summarizing how Tokum grounding extends JEPA with measurement anchors, cryptographic identity, and thermodynamic constraints
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Complete technical brief on Grounding JEPA with topological punctures, cryptographic verification, and thermodynamic constraints for AMI-scale deployment.

Grounding JEPA 15 Slides by Eric Blaettler
🔑 Key Concept

TOKUM — The Universal Semiotic Unit

A TOKUM is a frozen cryptographic identity (SHA-256 hash) functioning as a Peircean Sign. All semantic components—CCIs, CPIs, Interpretants, CTIs, and SSTs—are tokums.

Each parameter of the model is a tokum: a triadic structure linking representamen (hash), object (referent), and interpretant (contextual meaning).

CCI Tokum - Immutable Concept Identity
Semantic IP / DNA

CCI Tokums

Canonical Comprehension Identity: Immutable concept identities (SHA-256 of URN). The "IP address" or "DNA nucleotide" of meaning—global, routable, vendor-independent. Prevents concept drift and catastrophic forgetting.

CTI Tokum - Verified Measurement Anchor
Semantic MAC / Protein

CTI Tokums

Contextual Tokum Instance: Verified measurement anchors (SHA-256 of triple + timestamp + source). The "MAC address" or "expressed protein" of meaning—physically grounded, time-stamped, auditable.

CPI + I Tokums - Smart Legos
Semantic BPE Pairs

CPI + I Tokums

Comprehension Pairs & Interpretants: Semantic molecules (CPI: subject-predicate pair; I: object). "Smart Legos" with DNA-like sticky ends enabling combinatorial assembly and causal emergence.

SST Tokums - Spacetime Types
Relationship Context

SST Tokums

Semantic Spacetime Types: Context types (Proximity, Sequence, Containment, Property). Define how tokums interact—the "protocol" governing semantic assembly.

GRN Behaviors - Living Network
Network Dynamics

5 GRN Behaviors

Gene Regulatory Network Dynamics: Homing (stability), Inflating (growth), Deflating (pruning), Spiky (attention), Steppy (crystallization). The tokum network breathes, learns, and evolves like living tissue.

The Peircean Triadic Sign

Peircean Triadic Sign Structure

Every tokum functions as a complete Peircean Sign—a triadic structure that unifies representamen (the cryptographic hash), object (the referent in reality), and interpretant (the contextual meaning). This is not just data: it is meaning made auditable.

The Problem Statement
The Ptolemaic AI Crisis: Current artificial intelligence remains trapped in what we term the Ptolemaic paradigm—adding epicycles (parameters, layers, computational scale) to fix predictions while fundamentally misunderstanding the underlying structure of intelligence. Large language models optimize perplexity through statistical next-token prediction, achieving remarkable fluency while remaining semantically ungrounded. This is not merely a technical limitation but a categorical error: treating intelligence as a scalable asset concentrated in centralized systems, measured by accumulated parameters, when nature demonstrates intelligence as distributed flow across autonomous agents maintaining homeostatic balance through cryptographically frozen tokum networks.
Ptolemaic AI Crisis Illustration
Topological Puncture Illustration

Topological Puncture & Triple Loss

We augment JEPA's loss with semantic grounding and hallucination penalties operating on tokum networks.

Triple Loss Function
Ltotal = LJEPA + λ·Lsemantic + μ·LAIF

Abstract consistency + tokum grounding + entropy penalty

Dual Addressing Illustration

Tokum Architecture & GRN Dynamics

All parameters are cryptographic tokums: CCI (IP/DNA), CTI (MAC/Protein), CPI+I pairs, SST types.

  • CCI tokums: Immutable concept identities (IP/DNA)
  • CTI tokums: Verified measurement anchors (MAC/Protein)
  • 5 GRN Behaviors: Homing, Inflating, Deflating, Spiky, Steppy
Physics of Meaning Illustration

Agapistic Influence & Thermodynamics

Intelligence as Flow
I = Σ wi·(dGi/dt)
Gravity for Tokum Networks
A(τ,h) = α·G + β·C + γ·H

Thermodynamic governance of meaning through tokum dynamics

AI Safety Illustration

AI Safety Report Alignment

Aligning tokum architecture with the International AI Safety Report 2026 requirements through cryptographic audit trails.

  • Systemic Safety & Risk Mitigation
  • Verifiable Tokum Audit Trails (SHA-256 provenance)
  • Active Refusal via AIF Thresholds
Benchmark Illustration

Architecture Comparative Study

Comparative analysis of Transformer, Hybrid, and Semiotic Web (tokum) architectures across efficiency and retrieval metrics.

  • Energy: 100,000x gain (1W vs 100kW)
  • Retrieval: O(1) Deterministic tokum lookup vs O(n²) Probabilistic
  • Sparsity: 99.75% sparse tokum matrix

Which Technical Brief Should I Read?

Your Question Recommended Brief Key Insight
"How do we fix hallucination?" Mathematical Brief Details Topological Puncture, Triple Loss, and Active Refusal mechanisms.
"How does tokum addressing work?" Network Brief Explains tokum architecture (CCI/CTI), biosemiotic dynamics, and GRN behaviors.
"What is the theory?" Physics Brief Defines Intelligence-as-Flow, thermodynamics, and Agapistic Influence.
"How do we ensure safety?" Safety Brief Covers systemic safety, cryptographic tokum audit trails, and compliance.
"Why not Transformers?" Benchmark Brief Benchmarks efficiency: 100,000x energy gain via sparse tokum architecture.

Questions & Collaboration

Interested in the technical implementation of tokum architecture? Reach out to discuss JEPA grounding, biosemiotic dynamics, and deployment strategies.

Contact Eric Blaettler
Tokum.ai | St-Prex, Switzerland | © 2026


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