Yaob
A model family by Fylume · first featured initiativeFylume’s proposed AI model family and first flagship initiative: a shared cognitive core with selectively activated domain modules, designed for efficient local inference.
What is Yaob?
Yaob is Fylume’s proposed AI model family and the lab’s first flagship initiative. It is a research vehicle for one idea: a small shared cognitive core plus specialised modules, activated selectively, could deliver useful capability on ordinary hardware.
Yaob has not been released. There are no published benchmarks yet.
See the routing idea
Type a question. The diagram shows which domain modules a simple router would select, and which stay asleep.
Illustrative simulation. The interactive demonstration needs JavaScript. It shows which domain modules a simple router would select for a question — for example:
- “Why did Napoleon lose at Waterloo?” → history, politics
- “Solve x² − 5x + 6 = 0” → math
- “How do mRNA vaccines train the immune system?” → biology, medicine
- “Why is my Python loop so slow?” → software, cs
- “Size a solar system for a small cabin” → elec, energy, math
One shared cognitive core
Yaob’s intended architecture uses one shared cognitive core responsible for general language and reasoning. The exploratory size target is approximately 1–10 billion parameters, subject to research and validation.
Specialised functionality is reached through domain-relevant network modules. These are not separate full conversational models running inside every node.
Design goals
- Efficient inference
- Local execution
- A shared cognitive core
- Modular specialised knowledge
- Selective activation
- Reduced redundant computation
- Configurable resource budgets
- User control
- Flexible future model sizes
- Competitive capability at lower computational cost — as a research question
How the architecture works
- A request reaches the shared core.
- A router estimates which domain modules are relevant.
- Only those modules participate; the rest stay inactive.
- Each module is a Three Cell Node: knowledge, thinking, reasoning.
- The core integrates their contributions into one answer.
Research status
Status: in research. The architecture is being designed and tested. No model weights are available, no benchmark results are published, and no hardware requirements have been verified.
Known limitations and risks
- Routing mistakes may reduce answer quality.
- Cross-domain questions are hard to split cleanly.
- Selective activation does not automatically reduce memory use.
- A small core may limit general reasoning ability.
- Every claim needs measurement on real hardware before it is made.
Visit the Yaob siteyaob.fylu.me