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# I Built a Tiny Computer Inside a Transformer

**[Towards Data Science](https://daily.dev/sources/tds)** · 18 min read · 0 upvotes · 0 comments

## Summary

A hands-on exploration of treating a transformer as a programmable machine rather than a trained system. By assigning hidden-state dimensions to program variables (like CPU registers), wiring attention heads as deterministic lookup tables, and using feed-forward blocks as local compute units, a simple program can be compiled directly into transformer weights without any gradient descent. The residual stream acts as working memory, each layer as a machine step, and slot reuse mirrors register allocation in traditional compilers. The post also discusses geometric speedups for attention lookups via convex-hull structures, and references Percepta's work on compiling a WebAssembly VM into transformer weights for practical deterministic execution inside LLMs.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://towardsdatascience.com/i-built-a-tiny-computer-inside-a-transformer/>

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---

Tags: [#llm](https://daily.dev/tags/llm), [#compiler](https://daily.dev/tags/compiler)

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