kanaria007 PRO
kanaria007
AI & ML interests
None yet
Recent Activity
updated a dataset about 8 hours ago
kanaria007/agi-structural-intelligence-protocols posted an update about 8 hours ago
✅ Article highlight: *Incentives in Structured Intelligence* (art-60-045, v0.1)
TL;DR:
Most serious systems already run on incentives — budgets, tariffs, subsidies, penalties, and scarce-resource allocation. The problem is that these usually live outside the runtime as opaque spreadsheets, billing rules, or political defaults.
This article sketches how to make incentives *first-class inside SI-Core*: attach *BudgetSurface* and *CostSurface* to GoalSurface, run *ETH-aware tariff experiments* under PoLB, and treat pricing / allocation as auditable structured decisions rather than hidden knobs.
Read:
https://huggingface.co/datasets/kanaria007/agi-structural-intelligence-protocols/blob/main/article/60-supplements/art-60-045-incentives-in-structured-intelligence.md
Why it matters:
• makes economic trade-offs explicit instead of burying them in billing logic or policy spreadsheets
• prevents incentives from quietly fighting safety, fairness, or affordability goals
• lets tariff changes and budget-heavy actions be evaluated, simulated, and gated before rollout
• keeps pricing and allocation auditable with portable artifacts and normalized verdicts
What’s inside:
• *BudgetSurface / CostSurface* as typed attachments to GoalSurface
• *IncentiveLedger* for budgets, tariffs, exceptions, and compliance traces
• *PoLB modes for tariffs*: sandbox, shadow, and online rollout
• *ETH-aware A/B* for affordability and burden-by-income-band checks
• *Goal markets* for scarce resource allocation without reducing everything to tokens
• *Price discovery* as an E-Jump problem under welfare, fairness, and stability constraints
Key idea:
A serious intelligence runtime should not treat incentives as external afterthoughts. Budgets, tariffs, and price signals should be *observable, governable, and replayable* inside the same structure as safety and fairness.
posted an update 2 days ago
✅ Article highlight: *Federated SI* (art-60-044, v0.1)
TL;DR:
Most real systems do not live inside a single SI-Core. Cities, hospital networks, grid operators, transit systems, vendors, and neighboring institutions all run under different governance, trust, and legal boundaries.
This note sketches *Federated SI*: how multiple SI-Cores coordinate without pretending to share one brain. The focus is on portable artifacts, explicit trust boundaries, negotiated goals, limited memory exchange, and graceful failure when cooperation partially breaks.
Read:
https://huggingface.co/datasets/kanaria007/agi-structural-intelligence-protocols/blob/main/article/60-supplements/art-60-044-federated-si.md
Why it matters:
• makes cross-operator coordination explicit instead of hiding it inside ad hoc APIs
• supports cooperation under separate trust anchors, legal regimes, and policy surfaces
• treats failure modes seriously: partitions, vetoes, degraded cooperation, partial visibility
• keeps governance portable via normalized verdicts, pinned bindings, and export-safe artifacts
What’s inside:
• why “one SI-Core sees everything” is the wrong default
• federation objects such as federated SIRs, goal surfaces, memory views, and consent records
• negotiation across cities, hospitals, utilities, and other institutional stacks
• operational labels vs exported governance verdicts (`ACCEPT / DEGRADE / REJECT`)
• deterministic, auditable exchange rules for cross-run / cross-vendor comparison
• failover, mutual aid, and graceful degradation when trust or connectivity breaks
Key idea:
Intelligence at institution scale is not a single runtime. It is a *federation of governed runtimes* that must negotiate, coordinate, and fail safely without collapsing auditability.Organizations
None yet