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Recent Activity
posted
an
update
1 day 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
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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*.
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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
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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
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📖 Structured Intelligence Engineering Series
this is the *how-to-think / architecture sketch* layer for applying SI-Core to civic infrastructure.
published
an
article
1 day ago
CityOS Under SI-Core: A Worked Example Across All Invariants
posted
an
update
3 days ago
✅ New Article: *Structural Observability* (v0.1)
Title:
🔎 Structural Observability: Traces, Coverage, and Postmortems
🔗 https://huggingface.co/blog/kanaria007/structural-observability
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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*.
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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)
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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)
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📖 Structured Intelligence Engineering Series
this is the *how-to-design / how-to-operate* layer for traces that survive real incidents.
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