OpenSimula, an open-source Python implementation of the Simula mechanism-design recipe for controlled synthetic-data generation, has been added to the AfterImage dataset tool.
Hi r/MachineLearning, We added **OpenSimula** to our open-source dataset tool **AfterImage**: an experimental Python implementation of the **Simula** mechanism-design recipe from Davidson et al. (TMLR, [PDF](https://openreview.net/pdf?id=NALsdGEPhB); framing also in this [research blog](https://research.google/blog/designing-synthetic-datasets-for-the-real-world-mechanism-design-and-reasoning-from-first-principles/)). **Problem it targets:** For some SFT/eval setups you care less about “one prompt → one answer” and more about controlled diversity over a reasoning space: which axes of variation exist, how you joint-sample them, and how you stress-test generations before they land in a JSONL file. **What the code actually does (high level):** LLM-built **factor taxonomies** → **weighted mix sampling** over factors → **meta-prompt** diversification (+ optional complexification) → **requirement critic** loop with refinement → optional **double-critic** gate for **verifiable MCQ**. Artifacts are a versioned `opensimula/` checkpoint (manifest, taxonomy bundle, sampling strategy) plus append-only JSONL for accepted points. You can plug in the same `GenerationMonitor` we use elsewhere for observability into generation metrics, or bridge scenarios into `ConversationGenerator` via a small callback. **Hard disclaimers (please read):** * This is not a Google product, not a reference port of anything internal—just our read of the published recipe in the paper. * API is explicitly experimental and may change. * Cost and latency explode if you remove the caps on taxonomy width/depth; wide trees are many structured calls unless you tune bounds. * “Mechanism design” here helps structure the data-generating process; it does not magically fix model collapse or bad teacher models. **Code & docs:** * Repo (whole library): [https://github.com/altaidevorg/afterimage](https://github.com/altaidevorg/afterimage) * Simula examples: [https://github.com/altaidevorg/afterimage/tree/main/examples/simula](https://github.com/altaidevorg/afterimage/tree/main/examples/simula) * Short overview: [https://afterimage.altai.dev/opensimula.html](https://afterimage.altai.dev/opensimula.html) * API reference: [https://afterimage.altai.dev/api/simula.html](https://afterimage.altai.dev/api/simula.html) I genuinely would love hear your feedback if any.
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