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OpenBMB· @OpenBMB · X·· 2026-09-21AI 评分47
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面壁智能转发 @aijoey 的研究智能体设计:GPT-6 负责编排,MiniCPM5-2B 在 DGX Spark 上本地读取来源并提取可追溯证据。该应用名为 Footnote,首个研究问题产出 21 个来源、31 条论断和 11 个未解问题,点击论断可查看原文段落,点击关联可查看 AI 推理依据。下一步实验是用 AEON Qwen 27B 在第二台 Spark 上接管编排。

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Love this research-agent design from @aijoey: GPT-6 orchestrates while MiniCPM5-2B runs locally on DGX Spark to read sources and extract traceable evidence. A strong example of pairing frontier reasoning with compact, efficient models for transparent research workflows. 🔍

引用Joey@aijoey
Been putting MiniCPM5-2B to work on my DGX Spark. Built an app called Footnote that turns a research question into a living map of evidence. The setup: • Astra orchestrates through Codex CLI • MiniCPM5-2B workers read sources and extract quoted findings locally • Astra reviews the findings and connects them, with its reasoning visible First question: what’s keeping robots from being useful in ordinary homes? 21 sources. 31 claims. 11 unanswered questions. Click a claim and read the source passage. Click a connection and see why the AI made it. Live tokens/sec and concurrency are visible too. Then we added another paper. The map updated, and the original version stayed intact. All that extraction work from a 2-billion-parameter model. Next experiment: the AEON Qwen 27B model on my second Spark taking over orchestration. Already tested basic tool calls. A full local run is next. Building this one step at a time.
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来源:OpenBMB · x.com