Episode 1: Foundations with ADK – Foundations in AI agent development using the ADK.

Episode 1 of 5 in the AI agent development series focusing on foundations with ADK, MCP, and A2A. Includes theory, live coding, and Q&A.

Episode 3: Hierarchical Agents & Orchestration.

Episode 3 of 5 covering hierarchical agents and orchestration.

Episode 5: Multi-Agent Systems & A2A Protocol.

Episode 5 of 5 covering multi-agent systems and the A2A protocol.

This meetup is a space for developers actively working with any open-source AI libraries, frameworks, or tools, to share their projects, challenges, and solutions. Whether you're building with LangChain, Haystack, Transformers, TensorFlow, PyTorch, or any other open-source AI tool, we want to hear from you. This meetup will provide an opportunity to connect with other developers, share practical tips, and get inspired to build even more with open-source AI on Google Cloud. Come ready to contribute, and let's learn from each other!

Always wanted to get started with open source LLMs? Meta's Llama models are among the most popular and best performing in the world – and you can find them in Vertex Model Garden. In this session, we'll cover everything you need to know about working with Llama models on Vertex, from prompting best practices to choosing the best deployment method for your use case. With practical demos and real-world examples, discover how Llama can power your startup.

**Please bring your laptop to get the most out of this hands-on session**

Concerned about the quality and reliability of your generative AI models? Join us in this session if you understand the critical role of evaluation in development. Learn from Google and industry experts as we focus on how the Vertex AI evaluation service helps you validate every stage of the life cycle for quality and trust.

Explore the process, technology, and innovations behind Deepseek with expert-led tech talks

Explore the process, technology, and innovations behind Deepseek with expert-led tech talks.

Continuous Deployment can be a roadblock in the MLOps lifecycle, often requiring custom pipelines and complex configurations. Solution? The new integrations of Google Cloud Deploy and Vertex AI revolutionizes machine learning (ML) deployment by automating the entire process, and makes it easy to roll back through idempotent releases. The groundbreaking integration of Cloud Deploy and Vertex AI lets you test, validate, and deploy your ML models in minutes, without writing a single line of code.

Click the blue “Learn more” button above to tap into special offers designed to help you implement what you are learning at Google Cloud Next 25.

Evaluating the quality of a model’s responses relative to other models is a top challenge in deployment. Vertex AI makes this easier with new evaluation capabilities that help you assign a score to the quality of a model response. In this session, you will learn how to use evaluation tooling, best practices to set up your task-based evaluation framework, and how to use explanations to build trust in your evaluation.

Click the blue “Learn more” button above to tap into special offers designed to help you implement what you are learning at Google Cloud Next 25.