Category: Amazon Machine Learning

This post describes how a multi-leg hybrid search architecture solves this problem by combining vector similarity and keyword matching across multiple embedding channels in a single query, with results spanning both live events (searchable within 90 seconds of broadcast) and VOD archives simultaneously.

As organizations adopt TAMS and cloud-centered workflows through the Amazon Web Services (AWS) Cloud-Native Agile Production (CNAP) program, the opportunity is clear: Make content discoverable by what it contains rather than how it was tagged. This post, which is Part 1 of a two-part series, describes how AI-powered ingestion pipelines analyze each piece of media at ingest time.

F1 worked with AWS to migrate petabytes of footage from ageing tape robots, in multiple formats and proxy files, into Amazon Simple Storage Service (Amazon S3) alongside the live footage from every new race. That gave the sport one durable home for its heritage: the F1 Video Archive. In April 2026, F1 upgraded the archive with a new Media Archive Discovery system. Working with Amazon Web Services (AWS), the team added Amazon Bedrock in a deliberately narrow role: a layer that reads a request in plain language, works out what it means, looks up any facts it depends on, and turns it into a precise search the archive can retrieve.

From the halls of the RAI to local gatherings in Amsterdam, conversations around this year’s International Broadcasting Convention (IBC Show) centered on AI and collaboration. A reported 41,225 attendees from 170 countries and 1,300 exhibitors attended the event, held September 11-14, 2026. Amazon Web Services (AWS) hosted hands-on demos of new services, in-depth sessions, and events that reflected the rapidly changing industry landscape.

In this post, we extend that foundation by providing a complete reference implementation on GitHub with deployment instructions so you can run the solution with your own content.

In this blog, learn how Amazon Web Services (AWS) Partner Bitmovin has developed the AI Session Interpreter powered by the Mistral 7B foundation model (FM) on Amazon Bedrock, a fully managed service that offers a choice of industry-leading FMs.

In this post, we share how the PGA TOUR automated their approach with an AI-powered profanity detection and filtering system built on Amazon Transcribe. The solution meant that experienced production staff could take on higher value creative and technical roles while improving detection speed and consistency.

Launched at NAB Show 2026, Xytech AI is the first step in a much larger vision: making the full depth of the Xytech media operations platform accessible through natural language.

In this post, we show how to build SENTINEL, an Amazon Web Services (AWS) pipeline that embeds a cryptographic provenance watermark into AI-generated audio at the point of synthesis and carries a verifiable chain of custody through a live-streaming media pipeline. This post covers the architecture, AWS service implementation, deployment approach, and engineering trade-offs we encountered while building SENTINEL.

In this blog, learn how the CNN Weather app delivers real-time weather summaries using AI/ML, alongside its trusted journalism.