AI Hypercomputer is a revolutionary system designed to make implementing AI at scale easier and more efficient. In this session, we’ll explore the key benefits of AI Hypercomputer and how it simplifies complex AI infrastructure environments. Then, learn firsthand from industry leaders Shopify, Technology Innovation Institute, Moloco, and LG AI Research on how they leverage Google Cloud’s AI solutions to drive innovation and transform their businesses.

APIs dominate the web, accounting for the majority of all internet traffic. And more AI means more APIs, because they act as an important mechanism to move data into and out of AI applications, AI agents, and large language models (LLMs). So how can you make sure all of these APIs are secure? In this session, we’ll take you through OWASP’s top 10 API and LLM security risks, and show you how to mitigate these risks using Google Cloud’s security portfolio, including Apigee, Model Armor, Cloud Armor, Google Security Operations, and Security Command Center.

Bring your laptop and join us for an interactive demo on how to apply large language models (LLMs) from the Vertex AI Model Garden to a business use case, and learn about best practices for monitoring these models in production. We’ll go through an exercise using Colab Enterprise notebooks and learn how to use out-of-the-box tools to monitor RED (rate, error, duration) metrics, configure alerts, and monitor the rate of successful predictions in order to ensure successful use of a Vertex AI model in production.

Firestore with MongoDB compatibility is a serverless database service  designed to maximize scalability, high availability and performance without the hidden costs of capacity planning. This session demonstrates the new Firestore with MongoDB compatibility capabilities and discusses how Dialpad has built an Ai-powered customer communications platform leveraging Firestore over the last 14 years to grow a successful, performant, reliable business.

Join us for an in-depth session on Firebase Genkit, an open source framework that simplifies the development of AI-powered applications. Discover how to use the Node.js and Go SDKs to build intelligent chatbots, multimodal content generators, streamlined automation workflows, and agentive experiences. We'll demonstrate how Genkit's unified interface seamlessly integrates Google's Gemini and Imagen models, self-hosted Ollama options, and a variety of popular models from Vertex AI Model Garden. 

Simplify real-time data analytics and build event-driven, AI-powered applications using BigQuery and Pub/Sub. Learn to ingest and process massive streaming data from users, devices, and microservices for immediate insights and rapid action. Explore BigQuery's continuous queries for real-time analytics and ML model training. Discover how Flipkart, India’s leading e-commerce platform, leverages Google Cloud to build scalable, efficient real-time data pipelines and AI/ML solutions, and gain insights on driving business value through real–time data.

Join us as we explore the exciting future of AI in gaming. This session will showcase how leading organizations are leveraging machine learning and other AI technologies to create next-generation games experiences. Discover how AI is shaping the evolution of gameplay, storytelling, and player interaction, and gain insights into the trends that will define the future of interactive entertainment.

Take part in the new SOC Experience – a view into real-world attack scenarios. Learn about the latest hacker tactics and how Google equips cybersecurity teams with the data, AI, and scalable analytics to detect and remediate attacks.

In this session, you’ll learn how to build an AI agent using MongoDB Atlas on Google Cloud in just 15 minutes. We’ll cover how to embed and store your data along with vectors in a single database; build a vector search index and run search queries; and implement an AI agent.

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In today’s global media landscape, localizing video content is key to reaching wider audiences. This session demonstrates how to build a robust, end-to-end AI video dubbing pipeline on Google Cloud—covering video ingestion, transcription, translation, captioning, voice cloning, voice synthesis, and quality checks. We’ll explore an architecture that seamlessly integrates GCP products and best practices, highlight market opportunities, and address key challenges in AI dubbing. Attendees will learn how to streamline workflows so users can simply submit their video and receive fully dubbed results. Join us to see how Google tackles dubbing hurdles to maintain its leading edge in global content localization.

Unlock your team's full potential with the power of Google Cloud training for partners. Explore the learning portfolio designed for partner practicioners including role-based learning paths, certification programs, skill badges, and more. Plus, we'll highlight the latest from the generative AI portfolio. Boost capabilities and drive customer success without compromising productivity!

As AI adoption accelerates, many enterprises still face challenges building production-grade AI systems for high-value, knowledge-intensive use cases. RAG 2.0 is Contextual AI’s unique approach for solving mission-critical AI use cases, where accuracy requirements are high and there is a low tolerance for error. 

In this talk, Douwe Kiela—CEO of Contextual AI and co-inventor of RAG—will share lessons learned from deploying enterprise AI systems at scale. He will shed light on how RAG 2.0 differs from classic RAG, the common pitfalls and limitations while moving into production, and why AI practitioners would benefit from focusing less on individual model components and more on the systems-level perspective. You will also learn how Google Cloud’s flexible, reliable, and performant AI infrastructure enabled Contextual AI to build and operate their end-to-end platform.

Build intelligent search with Vertex AI Embeddings. This hands-on lab explores text and multimodal embeddings (images & video), showing you how to transform data into numerical representations for enhanced search. Learn to create a simple e-commerce search system that finds products based on text, images, and videos.

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!

Experience the future of AI with Google Cloud! Speak with Agentspace experts to learn how it can provide conversational assistance and take actions based on your company’s unique information. See topic details for each time block here.

Experience the future of AI with Google Cloud! Speak with customers who are building innovative AI solutions and learn directly from them. This experience offers a real-world look into "how we built it" discussions, giving you the chance to explore the possibilities. See detailed schedule of each timeblock here.

Tired of generic code suggestions? Learn how to customize Gemini Code Assist using your source code repositories. This session covers best practices for generating new code, and retrieving and reusing existing code, with Gemini Code Assist code-customization capabilities. Boost productivity, enforce consistency, and reduce cognitive load with a truly personalized AI coding assistant.

Unlock the power of generative AI with retrieval augmented generation (RAG) on Google Cloud. In this session, we’ll navigate key architectural decisions to deploy and run RAG apps: from model and app hosting to data ingestion and vector store choice. We’ll cover reference architecture options – from an easy-to-deploy approach with Vertex AI RAG Engine, to a fully managed solution on Vertex AI, to a flexible DIY topology with Google Kubernetes Engine and open source tools – and compare trade-offs between operational simplicity and granular control.

Explore how distributed cloud solutions solve for computing in sensitive on-premises, harsh, and remote environments with stringent regulatory and sovereignty requirements. Learn how these solutions enable secure access to advanced cloud capabilities like data analytics and AI within completely isolated environments, ensuring strict compliance and data residency. Key implementation and management considerations will be discussed.

Discover how some of the world’s most innovative companies modernized and transformed their applications with the power of Firestore, Firebase, and cutting-edge generative AI. Learn how they leveraged the latest technologies, such as edge computing and AI, to enhance customer experiences at every stage of the customer journey. Explore their innovative architecture and gain insights into building modern, engaging applications that deliver exceptional customer experiences.

This session explores the evolution of data management on Kubernetes for AI and machine learning (ML) workloads and modern databases, including Google’s leadership in this space. We’ll discuss key challenges and solutions, including persistent storage with solutions like checkpointing and Cloud Storage FUSE, and accelerating data access with caching. Customers Qdrant and Codeway will share how they’ve successfully leveraged these technologies to improve their AI, ML, and database performance on Google Kubernetes Engine (GKE).