Paper

ENF Technical Note 04

This technical note formalizes Embedded Neural Firmware (ENF) as a framework-level method for generating deterministic, sealed embedded intelligences from a compact design tuple. It defines ENF as a compile-time system: 𝐸𝑁𝐹(𝑇, 𝑃, 𝑆, 𝐹, 𝐶) → ℒ𝓈ℯ𝒶ℓℯ𝒹 where Task Complexity (T), Power Model (P), Security Level (S), Fallback Architecture (F), and Communication Scope (C) fully specify an agent whose behavior is fixed at manufacture-OS-free, offline by design, telemetry-free, and without OTA updates or dynamic allocation. The note introduces the ENF-Gene as a functional identifier that encodes the five- parameter ontology for cataloging, certification, reproducibility, and long-term auditability. A manifest-driven compiler pipeline is proposed (enf-manifest.yml) that deterministically emits sealed firmware plus cryptographic fingerprints (manifest.hash) and human-legible classification (agent.gene). Security is extended beyond digital integrity into the physical domain via an optional Dual-Gate activation mechanism that requires both PUF-derived identity validation and a factory-paired analog power-signature match prior to execution. The note further defines hybrid neural-formal agents as a practical default architecture, combining bounded symbolic safety envelopes with compact quantized inference for ambiguity handling while preserving analyzable timing, energy, and memory bounds. Finally, the document outlines application classes and a standardization direction for ENF as a taxonomy of permanent, privacy- preserving, single-purpose devices designed to remain trustworthy and reproducible over multi- decade lifecycles.