The AI Memory Problem: Why Long Context Isn’t Enough — Dan Biderman, Engram Co-founder & CEO
说话人分离结果（匿名标签）。同目录的
transcript.md未作任何改动。 标签 → 真人姓名的映射属于编辑判断，请记在 wiki 视频页开头，见 CLAUDE.md。 分离在抢话/串场处会错配：标签是证据不是判决，与内容矛盾时以内容为准。
说话占比¶
| 说话人 | 时长 | 占比 |
|---|---|---|
| SPEAKER_02 | 00:40:55 | 80.4% |
| SPEAKER_01 | 00:09:28 | 18.6% |
| SPEAKER_00 | 00:00:31 | 1.0% |
（访谈里占比低的通常是主持人，可作为认人的线索之一。）
说话轮次¶
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