How we think
Intelligence in nature is rarely centralized.
Our starting point is a research question, not a conclusion: can useful capabilities emerge from many smaller systems working together? It's the question behind the blueprint we're building for small language model design.
Simple interactions. Sophisticated behavior.
Nature frequently produces global behavior through local interactions. Ant colonies, flocking birds, fungal networks and cellular organization offer different examples of coordination without a single, all-knowing controller. These analogies are useful prompts for engineering—not proof that biology can be copied directly.
Smaller does not have to mean narrower in ambition.
Instead of asking one enormous model to perform every task, compact models may focus on specific capabilities: language, planning, retrieval, verification, safety or tool use. Specialization can make systems easier to evaluate, update and deploy.
The open question is how they work together.
We are studying how models can communicate, route tasks, critique outputs and combine evidence while keeping cost and latency in view. The quality of a collective depends on the interfaces and evaluations around it as much as on its individual parts.
Efficiency is a capability.
More efficient systems can support local deployment, privacy, multilingual specialization and constrained hardware. Modular systems may also allow one component to be replaced without rebuilding everything around it.
A note on research honesty
This is an active research direction, not a finished blueprint.
We are working toward one — publishing methods, failures and evidence as the small language model design blueprint takes shape.