Local intelligence
LLM, RAG and multimodal reasoning run within institution-controlled infrastructure.
PRIVATE • LOCAL • MULTIMODAL
Private AI,
human presence.
An offline AI-powered digital human for education and research—combining local intelligence, natural voice interaction and institution-controlled knowledge.
◉100% LocalProcessing stays on institutional infrastructure.
◇Private by DesignInstitutional data, policies and control.
▥Built to ScaleFrom a research prototype to shared use.
LOCAL INFERENCELLM · RAG · MULTIMODALInstitution controlled
VOICE PIPELINEASR · NLU · TTSNatural, low-latency dialogue
DIGITAL HUMANREAL-TIME PRESENCEContext-aware interaction
THE SYSTEM
One private intelligence layer.
Many human experiences.
MetaHuman is the independent research system. Hardware and display technologies are evaluated as components—not presented as project partners.
Natural interaction
Speech recognition, conversational AI and voice synthesis support fluid dialogue.
Digital human
A responsive, human-like interface makes complex material more approachable.
Immersive presence
Specialized displays can give the digital human a convincing physical presence.
WHY METAHUMAN
Designed for learning, discovery and trust.
EDU
Education
Course-grounded explanations, guided practice and accessible, multimodal learning support.
R&D
Research
A reproducible platform for human–AI interaction, digital-human and immersive-learning studies.
KNW
Institutional knowledge
Private access to approved policies, archives, research and instructional materials.
PROPOSED ARCHITECTURE
From institutional knowledge to embodied interaction.
01Institutional knowledgeCourse • research • policy
→02Local AI engineLLM • RAG • multimodal
→03Voice + behaviorListen • reason • respond
→04Digital presenceAvatar • immersive display
TECHNOLOGY EVALUATION
Two different roles.
Two independent discussions.
NVIDIA and Looking Glass are not presented as partners, either with MetaHuman or with each other. Their technologies are being evaluated separately for different layers of the proposed system.
COMPUTE LAYERDISCUSSION IN PROGRESS
NVIDIA
Candidate platform for local AI inference and real-time digital-human workloads.
- RTX PRO 4500 BlackwellEarly prototype and research workstation candidate
- RTX PRO 6000 BlackwellPotential scale-up path for larger and concurrent workloads
- Topics to validateModel size, latency, Unreal rendering, concurrency and total system cost
DISPLAY LAYERDISCUSSION IN PROGRESS
Looking Glass
Candidate immersive display for presenting the AI avatar as a physical digital presence.
- Hololuminescent DisplaysDisplay family proposed by Looking Glass for AI avatar use
- Integration focusReal-time avatar pipeline, viewing experience, dimensions and deployment
- Topics to validateContent pipeline, SDK/API, latency, multi-view behavior and cost
Important: Company names identify technologies currently under evaluation. No partnership, endorsement, procurement decision or joint solution is implied.
MEETING BRIEF
Questions that move the project forward.
- Can one workstation run the LLM, RAG, speech and real-time avatar concurrently?
- Which model sizes and quantization levels fit the RTX PRO 4500 versus 6000?
- What reference architecture and academic support can NVIDIA provide?
- What is the recommended prototype-to-campus scaling path?
- Which HLD size best supports a life-size or classroom AI avatar?
- How does Unreal Engine or a real-time rendered character connect to the display?
- What latency, format, viewing-angle and content constraints should we test?
- Is a pilot, developer support or research collaboration pathway available?
EDUCATION · RESEARCH · TECHNOLOGY COLLABORATION
Start a conversation.
Discuss a demonstration, research collaboration, technology evaluation or future pilot for the MetaHuman Offline AI System.