AI model, artifact and training
Model definition, artifact versions, training/fine-tune run, configuration, compute and data provenance. Weights are stored outside the public catalog.
Research draft, second pass
A second pass drafted this model: the structure a model of this thing needs, and what is known about it in the world. The line under this one says how the second half was obtained - researched against sources, or recalled without web access, in which case nothing here was read anywhere and every claim is a lead to verify. Unreviewed either way.
Bundle → Layer → Finding → Questions Missing, in the backlog
Not described yet. This gap is in the card backlog.
Note: Research contour: bundles not designed yet; questions are listed as open questions.
Classifiers Filled
- Family
- Enterprise profiles
- Category
- Enterprise subject
- Entry kind
- subject
- Domain
- EnterpriseAI
- Industry
- Cross-industry
- Tags
- EM-AI-02W3subjectAIModelModelArtifactTrainingRunTrainingConfigurationComputeAllocation
What it is Filled
Model definition, artifact versions, training/fine-tune run, configuration, compute and data provenance. Weights are stored outside the public catalog.
Why it exists Filled
Model definition, artifact versions, training/fine-tune run, configuration, compute and data provenance. Weights are stored outside the public catalog.
Distinguishing features Derived, awaiting review
- Training pins input versions
- The same name does not prove the same weights
- A compute grant is not Employment
What robots and AI may and may not do Derived, awaiting review
Must not
- Negative case: A new endpoint is treated as a newly trained model.
Note: Negative case of the research brief, not yet a rule for agents.
Moral aspects Missing, in the backlog
Not described yet. This gap is in the card backlog.
Owners Filled
Steward
Руководитель AI / исследований
Master systems
- Model registry
- experiment tracker
- eval store
Links to other meta-models Filled
neighbor
- EM-AI-01
- EM-AI-03
- EM-DAT-01
- EM-FIN-05
references
- WM-SFT-004 - conceptual-candidate
- WM-AI-007 - conceptual-candidate
- WM-AI-006 - conceptual-candidate
What else AI and robots need to interact with it Incomplete
Identity and identifiers required Derived, awaiting review
- AIModel
- ModelArtifact
- TrainingRun
- TrainingConfiguration
- ComputeAllocation
Direct properties not applicable Not applicable
Not applicable
Enterprise record contour: physical properties belong to referenced world models.
Recognition required Missing, in the backlog
Not described yet. This gap is in the card backlog.
Capabilities and actions required Missing, in the backlog
Not described yet. This gap is in the card backlog.
Hazards and failure modes required Missing, in the backlog
Not described yet. This gap is in the card backlog.
Standards and interfaces required Missing, in the backlog
Not described yet. This gap is in the card backlog.
Context of use required Missing, in the backlog
Not described yet. This gap is in the card backlog.
Sources Filled
- NIST AI RMF: context, evaluation and risk management
- PROV/SPDX: provenance of data, artifacts and actions
- Model registry/evaluation tooling practice; map system, artifact, run and endpoint
Open questions
- How to distinguish the architecture, a checkpoint and a deploy?
- Which inputs does reproducibility require?
- How to reflect access and use restrictions on training data?
- Установить границу и решение reuse/extend/new по действующим спецификациям.
- Подтвердить semantic crosswalk, права и source mastership.
- Выбрать immutable refs; провести проверки fixtures до заявления о публикационной готовности.
Machine files
Provenance
enterprise research programme · published-partial
Built from: enterprise/models/em-ai-02/brief.json
Still in Russian: suggested owner, blocking decisions, vercy candidates. Translate in research/enterprise/i18n/units.en.json.