ARL is a universal, vendor-neutral measurement standard — what the Technology Readiness Level scale is to technology, for AI. Tied to no model, runtime, or vendor. Every score has four required parts, each anchored in math or physics: validation depth (1–9), convergence class (A–E), energy profile (joules), security class (S0–S4). Cross-axis gates make a high readiness claim unreachable without matching convergence and security; energy/security non-disclosure caps the score. Lands the public 3-document stack (v1.2) — ARL.md (framework), ARL-S.md (sandbox/measurement environment), LEXICON.md (controlled vocabulary) — plus a README and CC-BY-4.0 LICENSE. The 4 internal documents (strategy, governance/benchmark catalogs, forecast model) are deliberately NOT included — public set only. Top-level README updated: ARL listed as a standard; the joules-as-shared- unit framing corrected (ARL is universal, joules is one of its four axes, not a shared substrate). A standalone, system-agnostic reference implementation (arl-core: the four-axis claim model with cross-axis gates + LEXICON vocabulary enforced) is next, and will carry Apache-2.0. Co-Authored-By: Claude Opus 4.7 <[email protected]>
30 lines
1.3 KiB
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30 lines
1.3 KiB
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Creative Commons Attribution 4.0 International
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Copyright (c) 2026 Transaction Science, Inc.
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This specification text and accompanying documents are licensed under the
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Reference implementations and software accompanying this specification, if
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and when published in this directory, may be released under a separate
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