docs(research): unify Hyphae positioning + 8-min pitch deck + federated learning#11
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…ed learning - hyphae/POSITIONING.md (new): 权威口径单一来源 — 产品化持续价值（非贴身服务）+ 运营合伙人分润 + 口碑闭环 + 找路径护城河 + 评估 - hyphae/PITCH_8MIN.md (new): 8 分钟产品介绍口述稿（真实数据引用，已修正） - hyphae/pitch_deck/ (new): 手绘风 10 页幻灯片 HTML + render.py + PDF + PPTX（中文手写体 + 小J） - hyphae-training/FEDERATED_LEARNING.md (new): 联邦学习专项 — FATE-LLM/FedML + FedALT 式个性化 LoRA（= 客户 LoRA + 行业 LoRA 同构） - 对齐旧文档去"贴身服务"口径：OUR_MOAT / README / OUR_PIPELINE_AND_BUSINESS / BP_5PAGES(+PDF) 🤖 Generated with Claude Code
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✅ APPROVE — Hyphae positioning unification + pitch deck + federated learning research
Scope: 13 files, documentation-only (markdown + rendered PDF/PPTX + HTML/render script). No source code, no contracts, no security surface.
Review (2-round, docs): DeepSeek R1 → Sonnet verdict.
Findings
[Low] render.py:1 — unused import→ false positive:globglobis used viaglob.glob()at line 28. No change needed.
No blocking issues.
Assessment
- POSITIONING.md establishes a clean single-source-of-truth for the商业口径 (productized value + operator-partner revenue-share + word-of-mouth loop, replacing the white-glove model).
- Old docs (OUR_MOAT / README / OUR_PIPELINE / BP_5PAGES) consistently aligned with banners pointing to POSITIONING.
- FEDERATED_LEARNING.md is well-grounded (FedALT-style personalized LoRA maps cleanly onto the existing 客户 LoRA + 行业 LoRA architecture; cited sources).
- Pitch deck: Chinese renders correctly, factual claims now cite Gartner/McKinsey.
Verdict: APPROVE. Clean docs PR, internally consistent.
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Summary
统一 Hyphae 商业定位口径 + 8 分钟 pitch deck（手绘风 PDF/PPTX）+ 联邦学习专项调研。
新增
对齐（去"贴身服务"口径，指向 POSITIONING）
性质
Test plan