Introduction
This post discusses how DPG Media utilized AI-powered processes with Amazon Bedrock and Amazon Transcribe to streamline their video publication pipelines. The focus is on enhancing metadata management for a better consumer experience.
Challenges in Metadata Management
In the beginning, DPG Media faced challenges in managing metadata efficiently due to varied content sources and quality. Manual screening processes were time-consuming and not scalable as the company expanded.
AI Implementation for Automation
To address these challenges, DPG Media decided to integrate AI techniques, specifically focusing on audio processing for cost-efficiency and quicker processing. They implemented Amazon Transcribe for transcription and utilized Amazon Bedrock for generative AI applications.
Generating Detailed Metadata
Through a combination of AI tools and existing metadata, DPG Media successfully generated accurate content descriptions, genres, moods, and other key metadata. They utilized high-performing models from Anthropic and Hugging Face to ensure precision.
Aggregating Metadata at Series Level
One critical requirement was to aggregate metadata at the series level to improve content recommendations for viewers. By feeding video-level summaries back through Amazon Bedrock, DPG Media achieved high-quality aggregated data in a cost-efficient manner.
Ensuring Metadata Quality
To evaluate the generated metadata, DPG Media employed reference-free LLM metrics to ensure accuracy and relevance. This approach allowed them to refine the metadata generation process and align with evolving business needs.
Balancing AI and Human Expertise
In their approach, DPG Media balanced AI-driven processes with human expertise by validating results generated by the pipeline with human input. This combination aimed to enhance capabilities while maintaining quality control over the metadata.
Conclusion
By implementing AI-powered processes, DPG Media aims to offer a more engaging user experience, improve content recommendations, and move towards more automated systems. This evolution in metadata management promises operational efficiency and alignment with modern consumption habits.
Leave a Reply