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Open-deepthink adds knowledge distillation for multi-agent AI evolution

Andrew, a developer, has released open-deepthink, a project that uses a Qualitative Neural Network (QNN) architecture for multi-agent AI collaboration. This system arranges agents in layers, allowing them to perform structured forward passes and then reflect on their performance. The latest update introduces a full knowledge distillation mode, enabling users to extract detailed developmental traces of LLM knowledge, including agent reasoning and evolutionary history, into structured JSON datasets. AI

IMPACT Enables deeper extraction and understanding of LLM knowledge, potentially aiding in fine-tuning and debugging complex AI reasoning.

RANK_REASON This is a software tool release from an individual developer, not a frontier model release or significant industry event.

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  1. r/LocalLLaMA TIER_1 English(EN) · /u/causality-ai ·

    5 Months Later: open-deepthink Now Has Full Knowledge Distillation Mode

    <!-- SC_OFF --><div class="md"><p>Hey <a href="/r/LocalLLaMA">r/LocalLLaMA</a>,</p> <p>Some of you might remember when I posted about this project back around September last year (it was called local-deepthink then). The core idea was to move past the usual flat multi-agent setup…