Developer Builds Low-Cost Epistemic Gate to Counter LLM Data Poisoning in Fine-Tuning

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An independent developer has created an 'epistemic gate' system designed to prevent data poisoning attacks during large language model fine-tuning. The project was tested across five different model architectures and orchestrated entirely on a 2006 Toshiba laptop at zero cost. The work spans 16 documented experiments, with fully reproducible code and notebooks published on Kaggle. Supporting materials include a technical whitepaper and a corrective manual with formal mathematical loss specifications. The developer is inviting indie researchers, developers, and startups interested in safe local fine-tuning to review and run the notebooks.

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