AWS Media Blog
Learn more: M&E chalk talk presentations from AWS re:Invent 2019
re:Invent Chalk Talks are a highly interactive content format, beginning with a short lecture delivered by an AWS expert, followed by a 45- or 50-minute Q&A session with the audience.
While these sessions are not recorded, we wanted to share the decks with you as they contain valuable technical details. If there are any topics you’d like to know more about, please leave a comment.
Media Solutions sessions
- MDS305 Breaking news: Deploy global content distribution in minutes
- MDS306 Building resilient live streaming video workflows
- MDS307 Streaming media workloads within the AWS Well-Architected Framework
- MDS312 Launch media workflows quickly with AWS Media & Entertainment solutions
- MDS408 Building and refining AI models with human-in-the-loop worfklows
MDS305 Breaking news: Deploy global content distribution in minutes
Learn how MediaConnect can be used to facilitate unplanned or late-breaking content distribution requirements and can be a viable alternative to over-provisioned and expensive distribution infrastructure.
MDS306 Building resilient live streaming video workflows
Learn how to use the AWS Cloud and AWS Media Services, like AWS Elemental MediaLive, AWS Elemental MediaConnect, AWS Elemental MediaStore, and AWS Elemental MediaPackage, to build highly available and reliable live video workflows in a cost-effective and scalable way, complete with monitoring, alerts, and security.
MDS307 Streaming media workloads within the AWS Well-Architected Framework
AWS solutions architects examine streaming media workloads alongside the architectural pillars and best practices found within the AWS Well-Architected Framework.
MDS312 Launch media workflows quickly with AWS Media & Entertainment solutions
Learn about the suite of AWS Media & Entertainment solutions designed to provide a fast, easy path to launching media workflows.
MDS408 Building and refining AI models with human-in-the-loop workflows
Learn about the creation, labeling, and maintenance of a dataset, as well as the use of human-in-the-loop validation to manage results with low confidence scores and improve the dataset to further refine the ML models.
Additional M&E related sessions
- AIM222 Monetizing text-to-speech AI
- Next-gen video: Transcription, translation & search, powered by ML
- How developers can build natural, extensible voice conversations
- Optimize video processing using Amazon FSx for Lustre
- Archiving media content with Amazon S3 Glacier Deep Archive
AIM222 Monetizing text-to-speech AI
With a focus on on Amazon Polly, a machine learning–powered service that produces lifelike speech, learn to monetize this capability and generate a positive ROI when creating Amazon Polly applications.
AIM340 Next-gen video: Transcription, translation & search, powered by ML
The Media Analysis Solution on AWS uses Amazon Rekognition for facial recognition, Amazon Transcribe to create transcripts, Amazon Comprehend to run sentiment analysis on the transcripts, and Amazon Translate to make content available in multiple languages. This deck will show you how to upload your media files and work with the metadata that is automatically extracted through these services.
ALX201 How developers can build natural, extensible voice conversations
Learn how to use Alexa Conversations to create flexible, multi-turn experiences for use cases like buying tickets, making recommendations, ordering transportation or food, and making reservations.
STG349 Optimize video processing using Amazon FSx for Lustre
Learn how customers are using FSx for Lustre for video editing and rendering workloads.
STG355 Archiving media content with Amazon S3 Glacier Deep Archive
Learn from AWS experts how to eliminate your tape and archive your media content on S3 Glacier Deep Archive.
Want to learn even more? Find all the published re:Invent decks here.