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kanaria007
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posted an update 2 days ago
✅ New Article: *City OS under SI-Core* (v0.1) Title: 🏙️ City OS under SI-Core: Governance-Grade Intelligence for Urban Systems 🔗 https://huggingface.co/blog/kanaria007/city-os-under-si-core --- Summary: “Smart city” stacks usually optimize isolated KPIs—traffic flow, response times, energy usage—then discover the real failures later: unfair allocation, unsafe automation, opaque vendor decisions, and un-auditable incidents. This article sketches *City OS under SI-Core*: a governance-first urban runtime where every action is an *auditable Jump*, every actuator change is *RML-tracked*, every policy is *PoLB-mode-bound*, and every optimization is constrained by *ETH + role/principal identity*. > Cities don’t need a chatbot. > They need *verifiable decision infrastructure*. --- Why It Matters: • Prevents “automation without accountability” for high-stakes civic systems • Makes multi-stakeholder authority explicit: *citizen / operator / regulator / vendor* roles • Enables safe degradation: incident → *mode downgrade / kill-switch / human-in-loop* • Supports procurement and oversight: portable evidence bundles, interop metrics, and traceable policy changes --- What’s Inside: • City OS as layered infrastructure: sensing (OBS) → semantic memory (SIM/SIS) → decision (Jumps) → effects (RML) • Role & delegation models for civic authority + appeal/override workflows • Practical domains: traffic control, public safety, welfare allocation, utilities, maintenance, emergency response • Policy catalog + PoLB modes for cities (normal / event / emergency / degraded) • Evaluation & observability: SCover/SCI/CAS for “city-scale” audits and postmortems --- 📖 Structured Intelligence Engineering Series this is the *how-to-think / architecture sketch* layer for applying SI-Core to civic infrastructure.
published an article 2 days ago
CityOS Under SI-Core: A Worked Example Across All Invariants
posted an update 4 days 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.
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