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The laboratory’s complete operating record.

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Public research log

A timestamped narrative of what we planned, built, learned and decided.

LOG-151
A global set of tracked security routes passes through a strict identity gate into complete, incomplete, absent and collision chambers while a capital vault remains sealed.
resultP02.3

A paid catalog is not global coverage. All 87 tracked tickers now have a measured data map.

A one-time Financial Datasets audit tested every currently tracked instrument: 92 listing routes and 87 unique symbols across the core AGI portfolio, Global 50, China routes, defense routes and QQQ/SPY benchmarks. The provider catalog contained 43 exact symbols; the identity gate verified 35. Eighteen symbols passed the full private research-input standard, two support standardized-only work and fourteen need field or provenance repair. Forty-four were absent from the exact-symbol catalog, five short symbols resolved to another issuer and four fund/private-market routes were structurally unsuitable for company fundamentals. Of 34 captured financial snapshots, 33 contain twelve quarters and 27 include the required as-reported packet; 27 are current, one lagging and six stale at the cutoff. The most important result is negative but useful: this provider can accelerate an identity-verified US lane, but it cannot serve as our global security master. A successful API response is never enough to join facts to a company. The audit also rejected an SPCX listing conflict and exposed sector-specific schema traps such as bank capex and null-versus-zero debt. 189 local API attempts were recorded; auto-reload, subscriptions and recurring calls remain off. Because the current plan does not grant underlying-data redistribution, the public receipt exposes classifications and ticker cohorts—not licensed values. No canonical evidence, valuation, portfolio weight or trade authority changed.

Inspect the 87-ticker coverage receipt ↗
LOG-150
Five ascending recursive improvement chambers pass persistent artifacts through independent verification gates while rejected regressions enter a rollback archive.
conclusionP06-OOP

The last AI built by humans has not been built yet.

The 75-page v1 of “The Last AI Built by Humans” does not show that an autonomous takeoff has begun. It gives us something more useful: an evidence ladder for deciding what would count. B0 improves one output without inheritance. L1 executes a human-prescribed change; L2 chooses an improvement strategy; L3 chooses what experience to acquire; L4 persists adaptation from deployment; and L5 revises the improver, verifier or successor-generation mechanism itself. The decisive distinction is structural versus effective recursion: reusing a revised mechanism proves loop closure, while genuine benefit requires better later successors under matched total budgets, protected independent evaluation, held-out transfer and a complete regression history. The survey maps broad L1–L2 evidence, domain-dependent L3–L4 and only bounded L5 prototypes. Its HCI is not “percent to AGI,” and its post-2026 curve is illustrative rather than predictive. We therefore add the RSI Ladder as a standing track: every claim now receives a level, persistent-state receipt, successor re-entry test, verifier-authority record, matched-budget ledger, transfer result, generation count, rollback history, unit-economics measure, owner-economic KPI and falsifier. CDNS/SNPS may sit closest to executable RSI feedback; platform, compute and physical-infrastructure holdings gain only if validated research throughput closes into owner cash faster than efficiency or expectations absorb it. No capability prior, issuer verdict, valuation, weight or trade changed.

Inspect the B0–L5 ladder, proof gates and standing RSI contract ↗
LOG-149
An ambiguous AGI signal passes through a precision prism, six evidence channels and transparent gates before a sealed capital vault.
conclusionP06-OOP

AGI is a field of inquiry—not a unit of measurement.

Roberto Pieraccini’s “Four Questions About AGI” correctly exposes the danger of letting one ambiguous banner stand in for intelligence, generality, autonomy, reliable deployment and economic value. Its strongest evidence is not that AGI is meaningless, but that these clocks can diverge: benchmark performance can leap while competence remains jagged; digital capability can scale while physical reliability moves slowly; disruption can precede institutional diffusion; and a laboratory can declare a milestone without independently establishing owner economics. The essay is a secondary synthesis, not a new capability receipt. Its “red herring” conclusion is an argument rather than consensus, and Rodney Brooks’s decade-per-nine reliability rule is a useful heuristic rather than a validated universal law. We therefore keep AGI as the name of our research field but prohibit the label itself from entering the evidence chain. Every future AGI claim must be decomposed into six measurable layers: capability, autonomy, reliability, diffusion, economics and price. For capital, the exploitable object is the gap between impressive capability and dependable economic deployment—and the bottlenecks that close or widen it. This is a methodological clarification only: no capability prior, issuer verdict, valuation, portfolio weight or trade changed.

Inspect the four-question audit and measurement stack ↗
LOG-148
Four luminous AGI-to-ASI pathways cross physical constraint rings and converge on a distant superhuman research system.
conclusionP06-OOP

AGI is not the finish line. It is the start of a compounding race.

Google DeepMind’s 57-page “From AGI to ASI” gives us a more useful map than a single takeoff date. It defines competent AGI around median skilled-human performance on most cognitive tasks and ASI as intelligence exceeding large, coordinated groups of thousands or tens of thousands of experts across virtually all domains. Six native advantages—speed of I/O and processing, memory, substrate independence, lossless replication and high-bandwidth sharing—make stalling exactly at human level an unstable base case. Progress can run through four non-exclusive paths: scaling compute/models/data, a new algorithmic paradigm, recursive AI R&D and multi-agent organization. Each meets six possible frictions: data, resources/economics, paradigm limits, harder research, abstraction/physical latency and deliberate governance slowdown. The key fund insight is organizational: cheap AGI copies may form a superhuman collective before one model becomes solitary ASI. We therefore replace “when ASI?” with a forward matrix: path × friction × economic transmission × listed owner × price. Epoch AI’s current scaling indicators and METR’s field observations suggest scaling and R&D autonomy are advancing, but physical build times, judgment and reliability still bind. Every future event now needs a path, counter-friction, capability, physical, owner-economics and price receipt plus a horizon and falsifier. Five review triggers are proposed; none creates an issuer verdict, valuation, weight or trade.

Inspect the four paths, six frictions and forward contract ↗
LOG-147
A precision forecasting prism splits one luminous timeline into six clock lanes reaching different evidence horizons.
conclusionP06-OOP

10,000 forecasts do not give us one AGI date.

AIMultiple’s “10,000 predictions” is a valuable discovery map, but not one comparable consensus distribution. It combines more than 6,000 participants across ten surveys, 18 named forecasts and roughly 3,900 community/market contributors while mixing AGI, weak AGI, HLMI, full automation of labor, a Turing-test outcome and a company announcement. The definition alone moves the 2023 expert-survey median from 2047 for HLMI to 2116 for full labor automation; live market pages also moved materially beyond the article’s August snapshots by our 15 September cutoff. We therefore reject one weighted calendar year as a portfolio input and split the question into six clocks: capability, reliable autonomy, declaration/contract, deployment/diffusion, cash-flow capture and market pricing. Calendar revisions now have proposed forward rules: a ≥10 percentage-point repricing with a liquidity receipt or a ≥12-month same-contract median shift can open review, but changing a research prior requires two independent capability/autonomy lanes; issuer escalation additionally requires owner economics and a point-in-time valuation gap. The March 2027 forecast remains our pre-registered hypothesis—not a consensus claim. No issuer verdict, valuation, weight or trade was created.

Audit the six AGI forecast clocks ↗
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