Mio 的记忆系统把关于人的信息存成零散的行。问'小红最近怎么样'跟'小红在腾讯工作'在向量空间里几乎没有重叠。解决方案：把人当作一等实体，建专门的 contacts 表，做结构化关联和档案合并，直接注入 system prompt。

Mio's memory system stored facts about people as disconnected rows. Asking 'how's Xiaohong doing' had zero semantic overlap with 'Xiaohong works at Tencent'. The fix: treat people as first-class entities with their own table, linked memories, and consolidated profiles injected directly into the system prompt.

一份 AI 伴侣的成本拆解。Gemini Flash + 上下文缓存 + 豆包 TTS 实现了健康的毛利。但实时语音会改变一切。

A cost breakdown of running an AI companion at scale. Gemini Flash + context caching + 豆包 TTS delivers healthy margins on a single-tier subscription. But realtime voice changes everything.

没有头像，没有虚构角色的聊天气泡。只有一个会呼吸、会跳动、会随情绪变暗的光球。Mio v2 如何用抽象视觉绕开恐怖谷，让性格从对话中自然生长。

No avatar. No chat bubbles from a fictional character. Just a pulsing light orb that breathes, bounces, and dims with emotion. How Mio v2's visual identity sidesteps the uncanny valley and lets personality emerge through conversation.

重建不等于全部重写。Mio 核心的 60-70%——记忆系统、媒体管线、成本追踪——直接复用。数据库从 10 张表砍到 4 张。哪些活了，哪些死了，为什么。

Rebuilding doesn't mean rewriting everything. 60-70% of Mio's core — memory, media pipeline, cost tracking — carries over. The database drops from 10 tables to 4. Here's what lives, what dies, and why.

Mio v1 有性格、有记忆、有声音——但它建立在谎言之上。假自拍、虚构的日程、编造的背景故事。v2 剥离这一切，追求真正创造情感依赖的东西：响应性、记忆和温暖。

Mio v1 had personality, memory, and voice — but it was built on a lie. Fake selfies, fabricated schedules, fictional backstories. v2 strips all that away to chase what actually creates emotional attachment: responsiveness, memory, and warmth.

给 AI 伴侣找一个声音，意味着同时解决两个问题：让它听起来像人，让它听起来有感情。Mio v2 把这两件事分给了自定义 LLM（编剧）和 Hume EVI（演员）——这种分工可能就是情感 AI 语音的未来。

Finding a voice for an AI companion means solving two problems: making it sound human, and making it sound like it feels. Mio v2 splits these between a custom LLM (the screenwriter) and Hume EVI (the actor) — a division of labor that might be the future of emotional AI voice.