Research index / Project guide
MiRust.com publishes structured research guidance and a source-grounded implementation map. It does not execute the browser runtime or transfer implementation observations into production, security, compatibility, or model-quality claims.
Project boundary: the project owner identifies GGUF.MiRust.com as a separate implementation project. MiRust.com remains the public guide, documentation, evidence model, and research index.
Current research and implementation tracks
GGUF.MiRust.com implementation audit
Code-level documentation of the reviewed TinyRustLM 0.1.0 workspace, custom SLM1 binary format, WebAssembly ABI, scalar transformer path, artifacts, tests, limitations, and next implementation gates.
Small-model runtime architecture
Loader design, tensor metadata, memory planning, quantization, tokenizer boundaries, KV caches, CPU and GPU dispatch, fallback behavior, and reproducible measurement.
Teleodynamic and resource-bounded systems
Two-timescale dynamics, endogenous resource coupling, local action evaluation, explicit no-op behavior, phase diagnostics, DE11, and the distinction between a research paradigm and verified implementation.
TinyLM-16M reference workload
A compact transformer profile used to explain operators, memory estimates, quantization, model containers, and test planning. Values remain proposals or externally reported estimates until independently verified.
Standard ML runtime case study
A compiler and virtual-machine case study covering parsing, Hindley–Milner inference, pattern compilation, closures, bytecode, arena-based object graphs, and an optional embedded diagnostic model.
Rust-oriented architecture
Traits as ports, focused adapters, enums for closed domains, typestate, newtypes, RAII, explicit errors, message passing, and bounded use of dynamic dispatch.
Enterprise delivery and governance
Dependency policy, supply-chain review, testing, observability, semantic versioning, MSRV policy, SBOMs, release signing, migration, and rollback.
How research becomes site content
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Intake
Record the source, owner, date, scope, and intended target page.
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Separate facts from proposals
Mark observed values, estimates, design hypotheses, and external reports explicitly.
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Publish a useful slice
Convert accepted material into a guide, documentation topic, roadmap item, evidence requirement, or correction.
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Verify before widening claims
Require compatible source revisions, environments, methods, and limitations before changing a status.
Research inputs in this release
The current starter content incorporates original summaries derived from reports on custom Standard ML runtimes, TinyLM-16M browser execution, teleodynamic AI, browser-local Rust runtimes, Rust design patterns, and enterprise governance. The reports are research inputs, not proof that the described systems exist or meet performance targets.
Explore Teleodynamic AI · Read the project boundary · Open research documentation