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AWS Elemental adds multiview, ad insertion to help broadcasters personalize and commercialize livestreams

Amazon Web Services Inc. is bringing artificial intelligence into live video streams within the AWS Elemental infrastructure service to help broadcasters meet viewers’ expectations of content-aware streaming and hyper-personalization. Announced ahead of this week’s IBC 2026 conference in Amsterdam, an event that showcases the latest advances in media, broadcasting and entertainment technology,…

AWS Elemental adds multiview, ad insertion to help broadcasters personalize and commercialize livestreams

Amazon Web Services Inc. is integrating artificial intelligence into live video streams within its AWS Elemental service to enable broadcasters to personalize and monetize their content. The updates, revealed ahead of the IBC 2026 conference in Amsterdam, encompass server-side dynamic multiview, real-time scene analysis, low-latency ad insertion, and automated ad yield optimization.

As the live streaming market has grown to over $100 billion, most platforms still struggle to meet viewer expectations for customizable camera angles, real-time personalization, and relevant ads. AWS aims to address these challenges by embedding machine learning and dynamic stream compositing into the core video pipeline of AWS Elemental, eliminating the need for multiple third-party integrations and reducing costs.

The new features include AWS Elemental MediaPackage Dynamic Multiview, which allows viewers to select camera angles from multiple feeds, AWS Elemental Inference Contextual Metadata for real-time scene-level metadata, AWS Elemental MediaTailor Yield Optimization for automated ad placement and monetization, and AWS Elemental MediaTailor Low-Latency Ad Insertion for targeted ad delivery in low-latency streams.

JioHotstar, an Indian livestreaming platform, is among the first broadcasters to utilize these features, providing subscribers with control over live sports viewing experience.

Written by urgent.news from SiliconANGLE's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.

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