Patrick Löber from Google DeepMind provides a technical walkthrough of the Gemini API's "any-to-any" capabilities. The session covers multimodal understanding of complex documents, video, and audio; an agentic loop using function calling to trigger native image and speech generation; and the real-time, audio-to-audio Live API.
Cormac Brick from Google's AI Edge team details the dual trends of on-device AI: large, system-level models like Gemma 4 enabling complex agent skills, and fine-tuned tiny LLMs for high-performance, in-app tasks. The summary covers the architecture of on-device function calling, the engineering trade-offs for edge deployment, and the practical workflow for fine-tuning and deploying models under 1B parameters on platforms like Android and iOS.
Bhuvaneswari Subramani details the "Agentic Shift" in AI by presenting an evolutionary journey through seven foundational system design patterns. The talk progresses from simple conversational clients to sophisticated, multi-agent systems, covering key patterns like Retrieval-Augmented Generation (RAG), Self-Correcting RAG, and the Model Context Protocol (MCP), explaining how each pattern adds new layers of context, action, and autonomy.
A deep dive into the evolution from static chatbots to dynamic, agentic AI systems. Philipp Schmid of Google DeepMind explores how to design, build, and evaluate AI agents that leverage structured outputs, function calling, and workflow orchestration with Google Gemini, covering key agentic patterns and the future of AI development.
Built-in tools like web search, file search, and code interpreter allow developers to extend model capabilities out-of-the-box. This summary covers the concepts, compares them to function calling, and details a demo of building a data exploration dashboard using multiple tools in concert.
A deep dive into building agentic systems using OpenAI's latest APIs. The session covers the core concept of 'agentic tool calling' (reasoning + tools), outlines a four-part framework (Agent, Infrastructure, Product, Evaluation) for designing long-horizon tasks, and provides a hands-on demonstration of building a non-blocking task processing system with a real-time progress UI.