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kanaria007
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posted an update about 4 hours ago
✅ New Article: *Structural Observability* (v0.1) Title: 🔎 Structural Observability: Traces, Coverage, and Postmortems 🔗 https://huggingface.co/blog/kanaria007/structural-observability --- Summary: When conventional systems fail, you dig through logs, metrics, and RPC traces. In a Structured Intelligence stack, that’s not enough—you need structural answers: *What did the system see ([OBS]) before acting? Which goal surfaces were active ([EVAL])? Which Jump/engine produced the decision? Which RML effects executed (and which compensators ran)? Which PoLB mode / release / experiment context was in force?* This article introduces *Structural Observability*: full-stack structured traces anchored on the *SIR* (episode record), plus cross-cutting *JumpTrace / RMLTrace / EvalTrace / EthicsTrace / GeniusTrace* so incidents can be replayed and explained—without hand-wavy storytelling. > Logs are strings. > Structural observability is *reconstructable decision anatomy*. --- Why It Matters: • Makes postmortems answerable: “what happened?” becomes *traceable structure*, not vibes • Turns key SI metrics into real operational signals: *SCover / SCI / CAS* • Prevents silent contradictions (e.g., “ETH blocked” but an effect still fired) via consistency checks • Enables deterministic re-runs and audit-grade bundles (portable, hashable, exportable) --- What’s Inside: • A full-stack trace model: World → OBS/SIM/SIS → *SIR* → JumpRuntime → RML Engine → Effects • How to design trace envelopes and coverage so *SCover* is meaningful • What “Structural Consistency Incidents (SCI)” look like in practice, and how to postmortem them • *CAS* and deterministic re-run routines (what must be pinned to get stable outputs) • Portability conventions for exported/hashed traces (canonicalization, no-float policies, scaled ints) --- 📖 Structured Intelligence Engineering Series this is the *how-to-design / how-to-operate* layer for traces that survive real incidents.
posted an update 2 days ago
✅ New Article: *Memory as Civic Infrastructure* (v0.1) Title: 🏛️ Memory as Civic Infrastructure: Retention, Forgetting, and Reconstruction 🔗 https://huggingface.co/blog/kanaria007/memory-as-civic-infrastructure --- Summary: In SI-Core, memory isn’t “just logs.” It’s closer to *roads and electricity*: everyone builds on it, it creates long-term externalities (privacy, fairness, institutional drift), and failures become structural. This article is a practical governance map for *what to retain, what to forget, and what (if anything) may be reconstructed*—across SIM/SIS, Genius Library, EvalTrace, and hash-chained AuditLog. > From raw → semantic → summarized → forgotten → (optionally) reconstructed. > Treat that lifecycle as policy— not an accident of your storage stack. --- Why It Matters: • Prevents “memory sprawl” turning into an unauditable, unerasable data lake • Clarifies what “erasure” means in an append-only world (tombstones, crypto-shred, erasable indices) • Keeps “genius reuse” without re-identification: *preserve structure, drop personal substrate* • Makes privacy trade-offs measurable via *originalness levels* + *reconstruction risk* + governance gates --- What’s Inside: • The memory map: *SIM / SIS / Genius Library / EvalTrace / AuditLog* and what each is for • A vocabulary for “originalness”: raw / semantic-reconstructable / structural-only / aggregate • Operations with crisp semantics: *erasure, redaction, aggregation, pseudonymization* • Policy skeletons that are exportable/auditable (canonicalization, digests, no-float conventions like bp/ppm) • Lifecycle governance hooks: approvals, audits, and safety/fairness constraints on forgetting --- 📖 Structured Intelligence Engineering Series this is the *how-to-think / how-to-govern* layer for memory as a civic substrate.
published an article 2 days ago
Memory as Civic Infrastructure: Retention, Forgetting, and Reconstruction
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