AI 导读
据 Pocket FM 称，Sherpa 背后的模型基于超过 1 亿小时的留存、金币消耗和流失数据训练。在公司自己对 176 道关于角色、事件顺序和情节的跨章节问题测试中，其故事记忆得分 89.8%，而图记忆基线为 57.4%。 草稿可本地化为七种语言，每季用一种声音旁白，并作为剧集发布到 Pocket FM。 来试试 👀 https://t.co/x1nViPsJnk
正文
According to Pocket FM, the model behind Sherpa was trained on more than 100 million hours of retention, coin spend, and drop-off data. On the company's own test of 176 cross-chapter questions about characters, event order, and plot, its story memory scored 89.8% against 57.4% for a graph memory baseline.
Drafts can be localised across seven languages, narrated with one voice per season and published to Pocket FM as an episode.
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来源：@testingcatalog · x.com