AI Deep Dive with Google (Ep 1)
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The Google AI Deep Dive Series is a hands-on virtual initiative designed to empower developers to architect the next generation of Agentic AI. Moving beyond basic prompting, this series guides you through the complete engineering lifecycle using Google’s advanced stack.
You will master the transition from local Gemini CLI environments to building intelligent agents with the Agent Development Kit (ADK) and Model Context Protocol (MCP), culminating in the deployment of secure, collaborative Agent-to-Agent (A2A) ecosystems on Google Cloud Run. Join us to build AI systems that can truly reason, act, and scale.
Tech Talk: Wrangling unstructured data with LLM-driven vector embedding
Speaker: Logan Hennessy (Google)
Abstract: The real world is big, messy, and full of unstructured data. Web pages, notes, and documents rarely fit into the rigid rows of traditional databases, making classic keyword search brittle and frustrating. To build tools that truly understand user intent, we must move past exact phrase matching and leverage semantic retrieval.
This webinar walks through how to build a lightweight search system using vector embeddings. We will focus on the mechanics of embedding and retrieval to turn raw, unstructured text into a highly queryable asset.
Walk away with a clear, practical framework for indexing unstructured data.
Venue:
Virtual, join from anywhere
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