基本信息
- 来源: blogs_podcasts
- 原始来源: https://aws.amazon.com/blogs/machine-learning/multimodal-embeddings-at-scale-ai-data-lake-for-media-and-entertainment-workloads
来源摘要/节选
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This post shows you how to build a scalable multimodal video search system that enables natural language search across large video datasets using Amazon Nova models and Amazon OpenSearch Service . You will learn how to move beyond manual tagging and keyword-based searches to enable semantic search that captures the full richness of video content.
We demonstrate this at scale by processing 792,270 videos from two AWS Open Data Registry datasets: Multimedia Commons (787,479 videos, 37-second average) and MEVA (4,791 videos, 5-minute average). Processing 8,480 hours of video content (30.5M seconds) took 41 hours. First-year total cost: $27,328 (with OpenSearch on-demand) or $23,632 (with OpenSearch Service Reserved Instances).…
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