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Leveraging AWS Generative AI Services for Dynamic Video Content Moderation and Policy Evaluation

Unlocking Opportunities with AWS AI and Generative AI: Media Analysis and Policy Evaluation Solution for Various Sectors

In today’s fast-paced digital world, organizations across various sectors need efficient solutions to extract information from videos and apply flexible evaluations based on their policies. Generative artificial intelligence (AI) has opened up new possibilities for these use cases, allowing for streamlined processes and enhanced capabilities. One such solution, the Media Analysis and Policy Evaluation solution, leverages AWS AI and generative AI services to meet these needs.

For advertising tech companies, ensuring brand safety, regulatory compliance, and engaging content is crucial when analyzing video content. This solution enables advanced content moderation, ensuring ads are placed alongside safe and compliant content to build trust with consumers. It also allows for the evaluation of videos against content compliance policies and the creation of compelling headlines and summaries to boost user engagement and ad performance.

For educational tech companies managing training videos, an efficient way to analyze videos is essential. This solution helps evaluate content against industry policies, index videos for efficient search, and perform tasks such as blurring student faces in recordings.

The solution is available on the GitHub repository and can be deployed to your AWS account using an AWS Cloud Development Kit (AWS CDK) package. It features a flexible and scalable architecture that can be integrated into existing pipelines or used as a standalone solution.

The solution includes components for media extraction and policy evaluation. The media extraction process involves preprocessing video content by extracting image frames and performing audio transcription. The extracted metadata is then used for policy evaluation using LLMs, allowing for dynamic policy assessments.

The microservice architecture of the solution follows best practices, with loosely coupled components that can be deployed together or independently. Users can access the frontend web application via Amazon CloudFront, upload videos to Amazon S3, and interact with the extract microservice through Amazon API Gateway. An AWS Step Functions state machine oversees the analysis process, transcribing audio, sampling image frames, and analyzing each frame using various ML models.

The solution also offers search functionality for efficiently identifying videos within an inventory and analyzing video data. Users can search for videos using text embedding, semantic search, and image search methods. The UI features a lightweight analytics interface for dynamic LLM analysis, providing users with the ability to test out different prompt templates for video analysis.

In conclusion, the Media Analysis and Policy Evaluation solution is a comprehensive and user-friendly tool for video analysis and policy evaluation. With its robust architecture and advanced features, organizations can streamline their video analysis processes and make informed decisions based on their policies. Deployable on AWS with a simple setup process, this solution is a valuable asset for organizations across various industries seeking efficient video analysis solutions.

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