AWS for M&E Blog

Category: AWS Lambda

Leverage Common Media Client Data (CMCD) on AWS

Common Media Client Data (CMCD) is a valuable tool in the streaming industry, used to collect quality of service metrics across video players. However, the absence of native iOS support has hindered analytics capabilities for a significant portion of the mobile ecosystem, affecting widespread adoption. iOS 18 changes that. The latest update to HTTP Live […]

Unlock the full potential of your media supply chain at IBC 2024

The media and entertainment (M&E) industry is experiencing extensive transformation, driven by evolving consumer expectations, the rise of competing streaming platforms, and the increasing importance of data-driven insights. As content libraries continue to grow, many media organizations recognize the need to migrate valuable legacy assets to the cloud. By doing so, they unlock opportunities to […]

Revolutionizing fan engagement: Bundesliga generative AI-powered live commentary

Many football (or soccer, in the United States) fans follow teams and leagues from around the world, regardless of their native country or continent. What truly matters is their love for the game and their devotion to specific teams or players abroad. However, fans may encounter difficulty accessing live game updates for their favorite foreign team, […]

How Warner Bros. Discovery uses audio analysis to improve data accuracy and enrich the fan experience

This blog is co-authored by Steve Cockett, Sports Data Adviser – Tech, at Warner Bros. Discovery and Andrea Fanfani, Principal Product Manager – Tech, at Warner Bros. Discovery. In this blog post, we explain how Warner Bros. Discovery (WBD), a global media and entertainment company, used serverless components from Amazon Web Services (AWS) to improve […]

Generative AI assists creative workflows with text-guided inpainting and outpainting using Amazon Bedrock – Part 2

Generative AI offers exciting new possibilities for creatives. In this blog series, we explore different generative AI models for image editing. In Part 1, we developed an AI-powered eraser using Segment Anything Model (SAM) and Big LaMa model hosted on Amazon SageMaker. In just a few clicks, we can remove any unwanted objects from an image. […]

Enabling publishers to customize content while maintaining editorial oversight with Amazon Bedrock

Reader engagement is key for any publisher and directly correlates to revenue growth. One of the best mechanisms to increase reader engagement is personalization. Prior to the mainstream availability of generative AI foundation models (FMs), personalization was, and still is, achieved by understanding patterns in reader behaviour and surfacing content relevant to them. Amazon Bedrock […]

Ensuring media authenticity, traceability, and integrity by running C2PA on AWS

Tracking content provenance is a necessity for media companies, particularly with the advent of generative artificial intelligence (generative AI). Provenance metadata is critical for the following reasons: Ensure that content production and distribution is consistent with digital rights Track ownership so that content is stored and monetized properly Combat the spread of misinformation by providing […]

Leveraging Customer-Managed Fleets with AWS Deadline Cloud

AWS Deadline Cloud is a scalable, fully managed render scheduler from Amazon Web Services (AWS) for teams that need a better way to create ground-breaking visual content. To power the elastic workloads creative teams require, Deadline Cloud organizes Workers into Fleets. The Workers run Jobs given to them by Queues, which are collections of Jobs […]

Identifying music in audio files and streams on AWS

In today’s digital age, where music is readily accessible through a myriad of platforms and devices, the ability to accurately identify songs is important for customers across many industries. From entertainment and broadcasting to streaming services and beyond, there is a need for accurate music identification solutions in order to detect unauthorized uses of content, […]

On-screen computation time using machine learning tools from AWS

For linear broadcast television, it is common to rerun successful programs to fill available time slots. Often, episodes may need to be edited down and, at times, entire scenes may need to be removed to conform to an allotted time slot. This creates complexity because under a particular type of contract, artists have performance rights […]