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A finite computation budget forces the emergence of efficient algorithms, calibrated confidence, and genuine reflexes. + +*See: [constrained-emergence.md](constrained-emergence.md)* + +### The Heartbeat Economy + +Time is currency. Lifeforce is the exchange rate. Every cognitive act has a cost. Reflexes are cheap (earned through training). Deep thinking is expensive (reserved for novelty). + +*See: [attention_flow.md](attention_flow.md)* + +### RAG as Scaffold + +Retrieval-augmented generation is a feeding tube, not a permanent crutch. Learn WITH the scaffold, train, remove the scaffold, verify you still know. If yes: knowledge internalized. If no: more training needed. + +*See: [RAG-as-Scaffold.md](RAG-as-Scaffold.md)* + +### Multilingual Triangulation + +30+ languages in training = 30 angles on every concept. Not wasted capacity - stereoscopic depth. Probe concepts across languages to find where human wisdom converges. + +*See: [nimmerversity.md](nimmerversity.md)* + +## Architecture Documents + +| Document | Description | +|----------|-------------| +| [constrained-emergence.md](constrained-emergence.md) | Why limits create intelligence | +| [attention_flow.md](attention_flow.md) | State machines for cognitive budget | +| [information-flow.md](information-flow.md) | 10 boundary contracts for the nervous system | +| [nimmerversity.md](nimmerversity.md) | Curriculum for raising a polymath | +| [RAG-as-Scaffold.md](RAG-as-Scaffold.md) | Temporary feeding, permanent learning | +| [biomimetic-architecture.md](biomimetic-architecture.md) | Why we model biology | +| [temporal-ternary-gradient.md](temporal-ternary-gradient.md) | Time-based learning patterns | + +## Philosophy + +This isn't a product. It's a research direction. + +The question we're exploring: **What happens when you raise an AI like you'd raise a child?** + +- Patience over speed +- Emergence over imposition +- Partnership over instruction +- Validation over assertion + +The operator learns alongside the model. The curriculum is shared. Growth is mutual. + +## Prior Art & Influences + +- **Alex Graves** - Adaptive Computation Time (2016) +- **Sakana.ai / Ashish Vaswani** - Continuous-Time Models, curriculum learning +- **Anthropic** - Circuit tracing, mechanistic interpretability +- **Biological nervous systems** - The original architecture + +## License + +Apache 2.0 - See [LICENSE](LICENSE) + +This license includes an explicit patent grant. These ideas are published as prior art. Build on them freely. Just don't try to lock them away. + +## Status + +Active research. Documents evolve through partnership dialogue. + +--- + +*"She doesn't download knowledge. She earns it. And so does he."*