34 lines
1.7 KiB
Markdown
34 lines
1.7 KiB
Markdown
## Salka Elmadani
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**Building [Inference-X](https://inference-x.com)** — better output from the same model.
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Universal AI inference engine. Fused computation, adaptive precision, surgical expert loading. 305 KB, 19 backends, zero dependencies. Built in Morocco for the world.
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### What I build
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| Project | What it does |
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|---------|-------------|
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| [**Inference-X**](https://git.inference-x.com/elmadani/inference-x) | Universal inference engine — 305 KB binary, 19 hardware backends, 23 quantization formats, fused dequant+dot kernels, Shannon entropy adaptive precision. Same model, cleaner signal. |
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| **ATLAS** | Open mathematical framework for neural network analysis. |
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| **Organ Architecture** | Neural network surgery — extracting, measuring, and grafting components between AI models to create functional chimeras. |
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### How it works
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The same model produces higher-fidelity output through Inference-X because the computation path is cleaner: fused kernels eliminate intermediate buffers, adaptive precision allocates depth where it matters, and surgical expert loading keeps only active parameters in memory.
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A smaller model running through a clean engine can outperform a larger model running through a noisy one.
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### Philosophy
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> *The best inference engine is the one you do not notice. You should hear the model, not the framework.*
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### Links
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[inference-x.com](https://inference-x.com) · [Documentation](https://docs.inference-x.com) · [Source Code](https://git.inference-x.com/elmadani/inference-x) · [Elmadani.SALKA@proton.me](mailto:Elmadani.SALKA@proton.me)
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---
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*Morocco*
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**→ [@ElmadaniSa13111 on X](https://x.com/ElmadaniSa13111)** · **[Support the project](SPONSOR.md)**
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