For media and communications organizations, the ability to rapidly discover, repurpose, and distribute content across platforms directly impacts revenue and audience engagement. This session examines how Generative AI is transforming content operations through intelligent metadata extraction, semantic search, and automated workflow orchestration. Using a case study from a global media organization managing 13 petabytes of content growing at 3,000 hours daily, we'll explore practical implementations using Amazon OpenSearch for multimodal retrieval, Amazon Neptune for knowledge graphs, and agentic AI for content assembly. Learn how organizations are achieving faster time-to-market, improved content monetization, and enhanced audience experiences through AI-powered content discovery and recommendation systems
What this session is about
Playbook
Editorial commentary · what to actually do about this on Monday
Independent editorial perspective — not an official AWS or speaker statement. Designed for executives evaluating what to brief their teams on next.
Live updates related to this session LIVE
Sourced via Parallel AI Monitor — continuous web watch on 21 topical streams. Updated .
- github.blog Agent memory & RAG architectures
Building an agentic memory system for GitHub Copilot
Researchers published a study of the gap between retrieving memories and using them faithfully in agent behavior. The work introduces a context-grounded evaluation of agentic memory and examines whether retrieved memories are actually supported by the current context, addressing
- research.google Agent memory & RAG architectures
ReasoningBank: Enabling agents to learn from experience
Researchers published a study of the gap between retrieving memories and using them faithfully in agent behavior. The work introduces a context-grounded evaluation of agentic memory and examines whether retrieved memories are actually supported by the current context, addressing
- github.com Agent memory & RAG architectures
I think the Agent should be able to learn from experience ...
Researchers published a study of the gap between retrieving memories and using them faithfully in agent behavior. The work introduces a context-grounded evaluation of agentic memory and examines whether retrieved memories are actually supported by the current context, addressing
- iternal.ai Agent memory & RAG architectures
Ultramemory: Agentic AI Memory for the Enterprise
Researchers published a study of the gap between retrieving memories and using them faithfully in agent behavior. The work introduces a context-grounded evaluation of agentic memory and examines whether retrieved memories are actually supported by the current context, addressing
- mdpi.com Agent memory & RAG architectures
From Retrieval to Faithful Memory Use: Context-Grounded ...
Researchers published a study of the gap between retrieving memories and using them faithfully in agent behavior. The work introduces a context-grounded evaluation of agentic memory and examines whether retrieved memories are actually supported by the current context, addressing
External links matched to this session via topic relevance. The KB does not endorse third-party content; verify before citing.