Building a Multimodal Deep Research Agent
How we went from "please find me information about this image" to building an AI that can reason across documents, videos, images, and audio like a digital Sherlock Holmes When Search Gets Visual Pic
How we went from "please find me information about this image" to building an AI that can reason across documents, videos, images, and audio like a digital Sherlock Holmes When Search Gets Visual Pic
Replace cookie-based targeting with privacy-first contextual signals, without blocking your auctions. The Problem Cookie deprecation is here. Third-party targeting signals are disappearing, and publi
Your search usually returns the wrong scene because of how the video was cut up before it was indexed. If you embed fixed time windows or every Nth frame, one vector can straddle two scenes, and the m
For contextual advertising, AWS gives you finished labels and Twelve Labs gives you stronger video models to build on. Amazon Bedrock Data Automation (BDA) splits a video into chapters and tags each o
The MCP servers an advertising agent needs fall into four groups. The ad platforms run their own servers for buying and reporting: Meta's Ads MCP at mcp.facebook.com/ads, Amazon Ads' MCP server (open
The current IAB Content Taxonomy is version 3.1, released in December 2024, with exactly 704 categories. GARM, the advertiser coalition behind the best-known brand safety categories, shut down in Augu
To run agentic search over a hierarchy of document clusters, first cluster the corpus: embed every document, then split the embeddings recursively into a tree, and give each cluster a label and a shor
You can keep your vectors in S3 and search them there. Three ways work today. AWS S3 Vectors stores embeddings in a special bucket type and answers similarity queries through an API. LanceDB writes a
Yes. Reverse video search exists, but the big search engines do not offer it as a single upload box. The usual workflow is to pull keyframes out of the video and run each one through a reverse image s