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gemini

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2020-Q1 2026-Q1

Activities

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This session showcases how Gemini Code Assist revolutionizes end-to-end Java application development. Join us to learn how to accelerate each development stage – from backend to frontend and testing. Discover how to leverage Gemini code generation, completion, and debugging features. Explore how to enhance productivity and build robust, high-quality applications faster. And take away practical methods and techniques for integrating Gemini Code Assist into your workflow.

Code assist tools are transforming software development, enhancing productivity with intelligent suggestions and automation. Yet they also pose challenges in ensuring code security, managing observability, and addressing risks from automation. Join experts from Google Cloud, Datadog, GitLab, Harness, and Snyk in a dynamic panel as they explore the potential of code assist tools and share strategies to mitigate risks, safeguard workflows, and maximize the impact of these tools in today’s fast-paced development landscape.

This session offers a technical deep dive of the state-of-art AlloyDB AI capabilities for building highly accurate and relevant generative AI applications using real-time data. We’ll cover vector search using Google Research’s ScaNN index technology and cover how you can utilize Gemini from AlloyDB operators to seamlessly integrate into your application. Discover AlloyDB AI natural language feature, a new way to interact with databases and how it accurately and securely answers your questions. Also learn about the latest research between Google and NVIDIA on GPU-accelerated vector index builds in databases.

How can organizations create scalable, engaging communications that capture attention and break through all of the noise? In the session, explore how the newest Google Workspace app is empowering teams of all sizes to build dynamic video content with Gemini to connect with coworkers and partners in new ways and break through the noise. Explore the latest customer insights, experience Vids in action, and discover what’s next.

Deploy and scale containerized AI models with NVIDIA NIMs on Google Kubernetes Engine (GKE). In this interactive session, you’ll gain hands-on experience deploying pre-built NIMs, managing deployments with kubectl, and autoscaling inference workloads. Ideal for startup developers, technical founders, and tech leads.

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

Unleash the power of Gemini with Vertex AI Studio. This hands-on lab guides you through using Gemini for image analysis, prompt engineering, and conversational AI, all within a user-friendly interface. Learn to design prompts and generate content directly from the Google Cloud console.

If you register for a Learning Center lab, please ensure that you sign up for a Google Cloud Skills Boost account for both your work domain and personal email address. You will need to authenticate your account as well (be sure to check your spam folder!). This will ensure you can arrive and access your labs quickly onsite. You can follow this link to sign up!

Are you ready to get hands-on with Google Cloud’s AI tools? In this 2 hour gHack, you will work in teams of 4. Together you will build a Formula E Race Analysis System from scratch using a variety of our AI and Data tools. Teams will work together to build the solution by searching, learning and collaborating together to find the answers needed. 3-2-1 lights out and away we go!

Concerned about AI hallucinations? While AI can be a valuable resource, it sometimes generates inaccurate, outdated, or overly general responses - a phenomenon known as "hallucination." This hands-on lab teaches you how to implement a Retrieval Augmented Generation (RAG) pipeline to address this issue. RAG improves large language models (LLMs) like Gemini by grounding their output in contextually relevant information from a specific dataset. Learn to generate embeddings, search vector space, and augment answers for more reliable results.

If you register for a Learning Center lab, please ensure that you sign up for a Google Cloud Skills Boost account for both your work domain and personal email address. You will need to authenticate your account as well (be sure to check your spam folder!). This will ensure you can arrive and access your labs quickly onsite. You can follow this link to sign up!

Faster AI innovation cycles often require MLOps – a critical, but complex, undertaking. Join us in this session to discover how a platform approach to MLOps on Vertex AI simplifies and accelerates the entire AI life cycle. Learn how to streamline development, deployment, and management of your AI models. We’ll also share real-world success stories from customers like GSK.

session
by Alex Braylan (Revionics) , Aakriti Bhargava (Revionics) , Derek Egan (Google Cloud) , Anand Iyer (Google Cloud) , Bryan Goodman (Ford Motor Company)

Ready to build production-grade AI agents to solve real-world challenges? Join us for a deep dive on the Vertex AI Agent Builder. Learn how to create sophisticated, multi-agent applications that combine generative AI with deterministic workflows. We'll cover key features including the Google Agent Development Kit (ADK), the Vertex AI Agent Garden, and the Vertex AI Agent Engine. We’ll show you how to build, deploy and monitor agents in production. You will also learn directly from customers about their agents built on Vertex AI.

session
by Hari Ramamurthy (The Home Depot) , Isabell Gruebner (AstraZeneca) , Lorenzo Spataro (Google Cloud) , Rocco Michele Lancellotti (RCS MediaGroup SpA) , Lavi Nigam (Google Cloud) , Greg Brosman (Google Cloud)

Want to create a retrieval-augmented generation (RAG) system perfectly tailored to your data and use case? This session dives into building custom RAG pipelines on Vertex AI. Learn how to combine Vertex AI services like document processing, vector search, and grounding to build powerful, context-aware AI applications.

Join this session to discover how a phone plan selection app, built with Flutter and Firebase, leverages Gemini 2.0 to enhance and simplify the customer experience. Gain insights into the technical architecture, identify actionable strategies to implement similar AI-driven solutions in your own apps, and understand the key principles of using AI to enhance the customer experience.

Language models have already evolved to do much more than language tasks, principally in the domain of image, audio, and soon video. Join Mostafa Dehghani to explore the emergent frontier of multimodal generation, what Gemini’s world knowledge unlocks that domain specific models cannot create, and how developers should be thinking about AI as a next-generation creative partner.

Learn how Database Migration Service can help you modernize your SQL Server databases to unleash the power of cloud databases and open source PostgreSQL! Convert your SQL Server schema and T-SQL code to PostgreSQL dialect with a click of a button in the DMS Conversion Workspace. Some objects could not be fully converted? Gemini can suggest a fix. Not yet familiar with PostgreSQL features? Ask Gemini to teach you how to convert SQL Server features to PostgreSQL equivalent ones. While Gemini is there - ask it to optimize the converted code or add some comments to explain the business logic. Once your database is fully converted and optimized you can migrate the data with minimal downtime using the change data capture powered migration job and complete your migration journey.

Audiences around the world have almost limitless access to content that’s only a click, swipe, or voice command away. Companies are embracing cloud capabilities to evolve from traditional media companies into media-tech and media-AI companies. Join us to discover how the cloud is maximizing personalization and monetization to enable the next generation of AI-powered streaming experiences for audiences everywhere.

Gemini was built from the ground up to support our breakthrough long context window, with up to 2 million tokens in our largest models. Join Nikolay Savinov to explore how to get the most out of long context and what a world of infinite context might look like.

Learn how to evaluate and optimize the impact of AI-assisted software development with Gemini Code Assist. This session covers processes for measuring AI-assistance effectiveness, exploring quantitative and qualitative measures available with Gemini Code Assist, and integrating with Cloud Monitoring and Cloud Logging. Discover how to leverage DevOps Research and Assessment (DORA) metrics to track productivity gains. Whether you’re a developer, team lead, architect, or IT manager, you’ll gain insights into measuring the impact of AI assistance.