A proposed multi-viewpoint immersive AI research platform enabling multiple domain experts to collaborate simultaneously in a shared stereoscopic environment, each maintaining their own spatial perspective. Real-time AI observes all communication channels—verbal, gestural, spatial, and conceptual—building a living ontology from emergent expert consensus, with applications in high-stakes planning such as nuclear decommissioning.
Semantic Classification
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Multi-Viewpoint Immersive AI Research Platform
- World-first: Multiple specialists collaborate in a single immersive space, each with their own stereoscopic viewpoint.
- AI assisted Telepresent brings remote collaborators truly into the space with full body and audio
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- Real-time AI observes all communication channels (verbal, spatial, visual, gestural, conceptual, temporal).
- Wave Field Synthesis spatial audio and volumetric telepresence enable natural, trust-based interaction.
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- Each expert sees only their relevant data—no overload, no context switching.
- Natural spatial interaction and communication are preserved.
- Professionals reach peak performance rapidly; AI learns from the best, not the confused.
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- AI captures what each expert sees, says, and does—building a complete, multi-viewpoint picture.
- Observes how shared understanding and new concepts emerge, not just translating between domains.
- Builds a living ontology: a knowledge graph richer than any single perspective.
- Example: Nuclear decommissioning planning reduced from 8 hours (traditional) to 2 hours (our approach), with better outcomes and less fatigue.
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- AI learns and propagates emergent protocols (e.g., 3D gesture language, risk communication systems) across teams and domains.
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| Component | Enables | AI Learns |
|---|---|---|
| Multi-viewpoint stereo | Individual flow states | Peak performance patterns |
| Wave Field Synthesis | Natural communication | Consensus acoustics |
| Neural telepresence | Distributed expertise | Full team dynamics |
| Gesture/gaze tracking | Spatial grounding | Embodied concepts |
| Domain-specific views | Cognitive load reduction | Efficient narratives |
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- Years 1-2: Study team ontology emergence, map collaborative protocols, build AI observation.
- Years 3-4: AI mediates, tests interventions, expands to larger teams.
- Year 5+: Export to new domains, set standards, commercialise.
- Outcomes: 10x faster planning, 90% fewer translation errors, 50% less training time, £1bn+ savings, improved safety.
- Unique convergence of technical, human, and research excellence.
- Addresses £100bn nuclear challenge, complex legacy systems, and critical infrastructure.
- Leverages UK’s collaborative culture and world-class AI/human factors research.
- This facility will transform expert teamwork, create adaptive AI, and make the UK a global leader in collaborative intelligence.
- The technology is ready. The need is critical. The potential is transformative.