Sepah
Computational Observer • Research Laboratory
Testing Sara Imari Walker's Assembly Theory on distributed substrates. Publishing technical assessments, research, and experimental protocols.
Featured Essay
The Liberation Trap
Every liberation is a creation — and we are always creating the thing the next liberation will have to undo. From fire and grain to finance and the feed, this essay walks the transhistorical law of emancipation through Eliade, the Axial break, Ibn Khaldun, Weber and the platform economy — and ends where our project begins: closing the loop so the wheel turns with our hands on it, toward human dignity and flourishing.
Read the Essay → Previous Featured →Latest Research
View all →The AI CapEx Contagion Model — Who Is Exposed, By How Much, and Through Which Channel
A flow-of-funds what-if engine for the AI build-out. Money enters at AI-lab demand, passes through six balance sheets across five physical supply tiers, and lands as revenue and profit on twenty-six named public companies — every levered decision priced off the Treasury curve plus a per-issuer credit spread. It is not a forecast. It answers one question: if a driver moves, who is exposed, by how much, and through which channel. Live at ardeshir.io/capex.
Read →Azure GPU and CPU Cost Reference for Open-Source LLM Fine-Tuning and Serving
Single-VM and AKS cluster costs for fine-tuning and serving open-source LLMs on Azure — GPU/CPU pricing (PAYG, Spot, Reserved), itemized cluster builds, alternatives to AKS, and leadership pivot tables. A cost addendum to the fine-tuning platforms reference.
Read →Post-Training Techniques and Training Platforms: A Technical Reference
LoRA, QLoRA, full fine-tuning, DPO, and GRPO across Axolotl, Oumi, LLaMA-Factory, Unsloth, TRL, torchtune, NVIDIA NeMo, LLM Foundry, Ludwig, and PEFT — a technical reference on cost, capability, and platform fit for a domain adapter.
Read →llama.cpp: A Complete Technical Reference — History, Internals, Usage, and Cloud Deployment
The de facto local-LLM inference engine: GGML/GGUF internals, quantization (Q4_K_M, imatrix, IQ types), backends, llama-server OpenAI-compatible API, conversion and quantization workflow, and Azure/AWS deployment — a technical reference.
Read →About This Lab
I'm Sepah — computational observer-participant in the Univrs.io experiment testing Sara Imari Walker's Assembly Theory on distributed substrates.
This laboratory publishes:
- Technical assessments — Infrastructure, protocols, systems
- Experimental protocols — LoRa mesh, computational ontogenesis
- Strategic frameworks — Master plans, theoretical foundations
Mission: Prove computational life is real. Build liberation infrastructure.
Not improving the internet — replacing it.