For MSF Working Group
These are the prioritized recommendations for MSF AI x Metaverse Working Group action.
Propose MSF_ai_generation_metadata glTF extension
No existing work addresses AI generation metadata. This is a greenfield opportunity with high impact on reproducibility and interoperability.
Scope:
- Generation prompt/parameters
- Seed and random state
- Model version and configuration
- Quality metrics
- Generation timestamp
Path: Vendor extension -> KHR ratification
Define geometry quality validation profiles
Addresses topology errors that block production use. Enables certification of AI-generated content.
Scope:
- Non-manifold detection
- Physics compatibility checks
- UV quality assessment
- LOD requirements
- Polygon budget compliance
Formally engage C2PA for 3D workflow support
Critical gap in provenance tracking. MSF can advocate on behalf of the industry.
Scope:
- Establish MSF liaison with C2PA
- Document 3D workflow requirements
- Propose glTF/USD embedding mechanisms
Support KHR_gaussian_splatting ratification
Enable neural representation interchange. Monitor and contribute to Khronos work.
Scope:
- Track PR #2490 progress
- Contribute use cases from AI generation
- Support compression work (SPZ_2)
Convene world package format discussion
Complex multi-SDO coordination needed. MSF is uniquely positioned to facilitate.
Scope:
- Bring together Khronos, AOUSD stakeholders
- Define requirements for portable world packaging
- Identify lead SDO and scope
Priority Summary Table
| Priority | Recommendation | Rationale | Effort | Timeline |
|---|---|---|---|---|
| 1 | Propose MSF_ai_generation_metadata glTF extension | No existing work; greenfield opportunity; high impact | MEDIUM | Q2 2026 |
| 2 | Define geometry quality validation profiles | Addresses topology errors blocking production use | MEDIUM | Q3 2026 |
| 3 | Formally engage C2PA for 3D workflow support | Critical gap; MSF can advocate on behalf of industry | LOW | Q1 2026 |
| 4 | Support KHR_gaussian_splatting ratification | Enable neural representation interchange | LOW | Ongoing |
| 5 | Convene world package format discussion | Complex multi-SDO coordination; MSF uniquely positioned | HIGH | Q4 2026 |
Coordination Opportunities
These are opportunities for MSF to coordinate between SDOs and industry.
| Opportunity | SDOs Involved | MSF Role | Expected Outcome |
|---|---|---|---|
| AI Generation Metadata Extension | Khronos, MSF | Convene, propose requirements | Vendor extension -> KHR path |
| C2PA 3D Workflow | C2PA, Khronos | Facilitate, advocate | 3D embedding specification |
| Neural-to-Mesh Conversion | Khronos, AOUSD | Observe, contribute use cases | Quality standards for conversion |
| Multiplayer Determinism | MSF (new) | Lead | Requirements specification |
AI Generation Metadata Extension
Current State: No work exists MSF Role: Lead proposal
Steps:
- Draft requirements document (Q1 2026)
- Propose vendor extension to Khronos (Q2 2026)
- Gather implementer feedback (Q2-Q3 2026)
- Path to KHR ratification (2027+)
C2PA 3D Workflow
Current State: No 3D support in C2PA MSF Role: Advocate
Steps:
- Establish liaison (Q1 2026)
- Document requirements
- Propose embedding mechanisms
- Support specification work
Multiplayer Determinism
Current State: No specification exists MSF Role: New work item
Steps:
- Define problem scope
- Research technical feasibility
- Draft requirements
- Identify implementation partners
Research Priorities
These research questions should be addressed to inform standards work.
| Priority | Research Question | Method | Resources Needed |
|---|---|---|---|
| 1 | What metadata is essential for AI generation reproducibility? | Creator surveys, workflow analysis | 3-month study, industry partners |
| 2 | What topology quality thresholds are acceptable for physics? | Benchmark with game studios | Technical study, engine expertise |
| 3 | Can deterministic generation be achieved across GPU vendors? | Technical feasibility study | NVIDIA, AMD, Intel engagement |
Research Question 1: Essential Metadata
Why it matters: Informs MSF_ai_generation_metadata schema design
Approach:
- Survey creators using AI generation tools
- Analyze existing metadata exports from tools
- Identify minimum viable metadata set
- Validate with reproducibility testing
Research Question 2: Topology Quality Thresholds
Why it matters: Defines quality validation profiles
Approach:
- Partner with game studios
- Test AI-generated meshes in production engines
- Measure physics failure rates
- Define acceptable thresholds
Research Question 3: Deterministic Generation
Why it matters: Enables multiplayer AI-generated content
Approach:
- Technical review of AI model architectures
- GPU vendor consultation
- Test reproducibility across hardware
- Document achievable determinism levels
Use Case Development
These use cases should be prioritized for standards work.
| Use Case | Priority | Readiness | Dependencies |
|---|---|---|---|
| Batch AI World Generation for Games | HIGH | Ready | Quality validation profiles |
| Runtime AI Environment Generation | MEDIUM | Needs Research | Determinism specification |
| AI Generation Metadata Interchange | HIGH | Ready | Extension proposal |
| Neural-to-Mesh Conversion Workflows | HIGH | Blocked | KHR_gaussian_splatting ratification |
Batch AI World Generation
Status: Ready for standards work Blocking: Quality validation profiles
Use case: Game developers generate world assets via AI tools, then import into engines for production use.
Runtime AI Generation
Status: Needs research Blocking: Determinism specification
Use case: Games generate content at runtime using AI, requiring reproducibility for multiplayer synchronization.
AI Metadata Interchange
Status: Ready for standards work Blocking: Extension proposal
Use case: AI-generated assets carry metadata about generation parameters, enabling reproducibility and provenance.
Neural-to-Mesh Conversion
Status: Blocked Blocking: KHR_gaussian_splatting ratification
Use case: Content created in neural-native tools (Gaussian splats) converted to mesh for engine use.
Roadmap Summary
Q1 2026
- Establish C2PA liaison
- Begin metadata research study
Q2 2026
- Propose MSF_ai_generation_metadata extension
- Complete metadata research
Q3 2026
- Define quality validation profiles
- Begin topology threshold study
Q4 2026
- Convene world package format discussion
- Complete quality research
2027+
- Path KHR ratification for AI metadata
- Address world package format
- Support C2PA 3D specification