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Recent Activity
posted an update 1 day ago ✅ Article highlight: *Robotics at the Edge* (art-60-052, v0.1)
TL;DR:
Robotics cannot treat SI-Core like a cloud-only governance layer. Physical systems need *hard real-time reflexes, local safety envelopes, degraded/offline behavior, and rollback tied to actuators*.
This article sketches *Embedded SI-Core* for robots, vehicles, drones, and other edge systems: keep *L0/L1 classical control*, add *L2 Edge SI-Core* for reflex Jumps and local ETH/MEM/ID, and use *L3 Fleet SI-Core* for planning, evaluation, and rollout.
Read:
https://huggingface.co/datasets/kanaria007/agi-structural-intelligence-protocols/blob/main/article/60-supplements/art-60-052-robotics-at-the-edge.md
Why it matters:
• keeps SI-Core compatible with millisecond safety constraints
• supports offline/degraded operation with local ETH capsules and ID envelopes
• makes physical rollback concrete via *RBL / RIR* and hardware-aware compensators
• treats robot updates as governed rollout problems via *PoLB*, not blind firmware pushes
What’s inside:
• *L0/L1 vs L2/L3* layering for embedded SI-Core
• *reflex Jumps* compiled for low-latency edge execution
• local *ETH capsules*, local *ID envelopes*, and degraded observation contracts
• physical *RML* with emergency-stop / safe-return compensators
• semantic compression at the edge instead of raw sensor firehoses
• rollout bands, digital twins, and fleet-safe policy updates
• WCET, fixed-priority scheduling, and safety-case integration
Key idea:
Robotics under SI-Core is not “LLMs on wheels.” It is a way to wrap physical control systems in *typed observations, explicit Jumps, local safety governance, and auditable rollback*.
repliedto their post 2 days ago ✅ Article highlight: *OrgOS Under SI-Core* (art-60-051, v0.1)
TL;DR:
Most firms already have an “operating system” of sorts — board meetings, budgets, OKRs, approvals, dashboards, launch processes.
What they usually do *not* have is a structured answer to:
*who is optimizing what, for whom, under which authority, with which replay and audit trail?*
This article sketches *OrgOS under SI-Core*: treat corporate governance itself as structured intelligence.
Read:
https://huggingface.co/datasets/kanaria007/agi-structural-intelligence-protocols/blob/main/article/60-supplements/art-60-051-org-os-under-si-core.md
Why it matters:
• makes board / CEO / BU / manager / union / regulator roles explicit
• turns major decisions into replayable *Jumps* instead of opaque meeting outcomes
• makes delegation time-bounded, scoped, and auditable
• lets firms run org changes, pricing changes, and incentive changes under *PoLB + EVAL* instead of vibes
What’s inside:
• *Firm GoalSurfaces* instead of fake single-number optimization
• explicit *roles, principals, delegation chains, and escalation paths*
• *SIM / SIS / SIR / EvalTrace / AuditLog* as corporate memory, minutes, and forensics
• board meetings as batched decision Jumps
• board resolutions and major programs as structured records
• normalized verdicts for exported governance artifacts
Key idea:
A serious firm should not run on spreadsheets, dashboards, and ad hoc approvals alone.
It should be able to say:
who decided, under what mandate, against which goals, with what evidence, and how that decision can be replayed, challenged, or corrected.
posted an update 3 days ago ✅ Article highlight: *OrgOS Under SI-Core* (art-60-051, v0.1)
TL;DR:
Most firms already have an “operating system” of sorts — board meetings, budgets, OKRs, approvals, dashboards, launch processes.
What they usually do *not* have is a structured answer to:
*who is optimizing what, for whom, under which authority, with which replay and audit trail?*
This article sketches *OrgOS under SI-Core*: treat corporate governance itself as structured intelligence.
Read:
https://huggingface.co/datasets/kanaria007/agi-structural-intelligence-protocols/blob/main/article/60-supplements/art-60-051-org-os-under-si-core.md
Why it matters:
• makes board / CEO / BU / manager / union / regulator roles explicit
• turns major decisions into replayable *Jumps* instead of opaque meeting outcomes
• makes delegation time-bounded, scoped, and auditable
• lets firms run org changes, pricing changes, and incentive changes under *PoLB + EVAL* instead of vibes
What’s inside:
• *Firm GoalSurfaces* instead of fake single-number optimization
• explicit *roles, principals, delegation chains, and escalation paths*
• *SIM / SIS / SIR / EvalTrace / AuditLog* as corporate memory, minutes, and forensics
• board meetings as batched decision Jumps
• board resolutions and major programs as structured records
• normalized verdicts for exported governance artifacts
Key idea:
A serious firm should not run on spreadsheets, dashboards, and ad hoc approvals alone.
It should be able to say:
who decided, under what mandate, against which goals, with what evidence, and how that decision can be replayed, challenged, or corrected.
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published an article about 2 months ago view article CityOS Under SI-Core: A Worked Example Across All Invariants
published an article about 2 months ago view article Memory as Civic Infrastructure: Retention, Forgetting, and Reconstruction
published an article about 2 months ago view article Policy Load Balancer: Risk Modes, Degradation, and Kill-Switches
view article Evaluation as a Goal Surface: Experiments, Learning Boundary, and ETH-Aware A/B
view article Role & Persona Overlays: Multi-Agent Identity in SI-Core
view article SI-Core for Individualized Learning and Developmental Support - From Raw Logs to Goal-Aware Support Plans
view article Proving Your SIL Code Behaves - Property Tests and Structured Checks for SIL / SIR / sirrev
view article Governing Self-Modification - A Charter for the Pattern-Learning Bridge
view article Digital Constitution for SI Networks - Auditable Law Above Many SI-Cores
view article Deep-Space SI-Core: Autonomy Across Light-Hours - *How an onboard SI-Core evolves safely while Earth is hours away*
view article Multi-Agent Goal Negotiation and the Economy of Meaning
view article Pattern-Learning-Bridge: How SI-Core Actually Learns From Its Own Failures
view article Auditable AI by Construction: SI-Core for Regulators and Auditors