Selected talks and presentations on AI agents, LLMOps, and building with Gemini.
▶Building Multi-Agent Pipelines with Google ADK
Orchestrating 8 specialized agents for retail site selection — from market research to strategy synthesis.
▶Build Live Voice Agents with Google's ADK
Building multi-agent AI applications with live voice input using Google's Agent Development Kit.
▶Async, Concurrency, and Batching: The Vertex AI LLMOps Trinity
The three capabilities you need to scale production LLM systems with Gemini and Vertex AI.
▶Context Caching and Controlled Generation with Gemini
Cost-efficient repeated queries and structured outputs using the Vertex AI Gemini API.
▶Building Multimodal RAG with Gemini
Leveraging Gemini's 2M context window and multimodal input for financial analysis Q&A.
▶The Gemini API: From Prototype to Production
From rapid prototyping in AI Studio to production-ready deployment on Vertex AI. Google I/O 2024.
▶Introduction to MultiModal RAG with Gemini on Google Cloud
Hands-on workshop: multimodal RAG on financial documents with text and images using Gemini Pro Vision.
▶Mastering MLOps: Building Future-Ready ML Systems
End-to-end ML lifecycle management — from experiment tracking to production deployment.
▶MLOps with Lavi Nigam (Part 1)
Foundations of MLOps — building reliable ML pipelines and deployment workflows.
▶MLOps with Lavi Nigam (Part 2)
Advanced MLOps — monitoring, retraining, and scaling ML systems in production.
▶Making Data Science Models Useful in Production
Integrating ML models into products — tools, techniques, and scalability best practices.