We address the problem of scaling up the production of media content,
including commentary and personalized news stories, for large-scale sports and
music events worldwide. Our approach relies on generative AI models to
transform a large volume of multimodal data (e.g., videos, articles, real-time
scoring feeds, statistics, and fact sheets) into coherent and fluent text.
Based on this approach, we introduce, for the first time, an AI commentary
system, which was deployed to produce automated narrations for highlight
packages at the 2023 US Open, Wimbledon, and Masters tournaments. In the same
vein, our solution was extended to create personalized content for ESPN Fantasy
Football and stories about music artists for the Grammy awards. These
applications were built using a common software architecture achieved a 15x
speed improvement with an average Rouge-L of 82.00 and perplexity of 6.6. Our
work was successfully deployed at the aforementioned events, supporting 90
million fans around the world with 8 billion page views, continuously pushing
the bounds on what is possible at the intersection of sports, entertainment,
and AI.

利用生成式 AI 模型，我们解决了大规模体育和音乐活动媒体内容（如评论和个性化新闻报道）的生产问题，并成功应用于 2023 年美网、温网和大师赛的自动化解说系统以及 ESPN Fantasy Football 和格莱美奖音乐艺术家故事的个性化内容创作，实现了 15 倍的速度提升，平均 Rouge-L 达到 82.00，困惑度为 6.6。我们的工作成功地支持了全球 9000 万球迷的 8 亿页面浏览，不断推动体育、娱乐和人工智能交叉领域的边界。