用AI让球迷和分析师用自然语言快速找比赛回放。
Agentic generative AI for media content discovery at the national football league
- 用自然语言查询代替传统筛选，自动拆解语义生成数据库指令。
- 准确率超95%，找视频时间从10分钟缩短至30秒。
- 适合体育媒体、内容创作者和赛事分析人员使用。
生成式AI为内容发现与管理带来了新可能。通过与美国国家橄榄球联盟（NFL）合作，我们展示了基于生成式AI的工作流如何使媒体研究人员和分析师能够使用自然语言查询相关历史比赛片段，而非传统的筛选点击界面。该智能代理工作流将用户查询分解为语义元素，并转化为底层数据库查询语言。通过精心设计的语义缓存机制，进一步提升了准确率与响应速度。系统实现超过95%的准确率，平均查找相关视频的时间从10分钟降至30秒，显著提升NFL运营效率，使用户得以专注于创作内容与构建精彩叙事。
原文摘要 · Abstract (English)
Generative AI has unlocked new possibilities in content discovery and management. Through collaboration with the National Football League (NFL), we demonstrate how a generative-AI based workflow enables media researchers and analysts to query relevant historical plays using natural language rather than traditional filter-and-click interfaces. The agentic workflow takes a user query as input, breaks it into elements, and translates them into the underlying database query language. Accuracy and latency are further improved through carefully designed semantic caching. The solution achieves over 95 percent accuracy and reduces the average time to find relevant videos from 10 minutes to 30 seconds, significantly increasing the NFL's operational efficiency and allowing users to focus on producing creative content and engaging storylines.
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