Discover how organizations are transforming into AI-applied companies. Explore strategies for optimizing, improving, and innovating GCP operations. Learn from a holistic approach to integrating GenAI, ML, and DataOps and the capabilities enabled for GCP strategy. Explore enhancements in serverless tech, automation, and security. Don't miss out on this opportunity to be inspired and informed.

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This session demonstrates how BigQuery ML connects all your data to cutting-edge AI using familiar SQL. Learn practical steps to build, train, and deploy machine learning (ML) models for predictive analytics directly in BigQuery while minimizing complexity and data movement. Discover ways to perform tasks such as sentiment analysis, audio transcription, and document classification with the latest models from Gemini, Claude, Llama, and others directly in BigQuery without the need for advanced Python or specialized ML skills.

Unlock the true potential of your enterprise data with AI agents that transcend chat. This panel explores how leading companies build production-ready AI agents that deliver real-world impact. We’ll examine Google Cloud, MongoDB, Elastic, and open source tools, including generative AI and large language model (LLM) optimization with efficient data handling. Learn practical approaches and build the next wave of AI solutions.

The size and volume of internet-based attacks continues to grow exponentially. From DDoS, bad bots, and fraud to data exfiltration and infrastructure vulnerabilities to new generative AI-specific attacks, having strong defense in depth for your internet-facing workloads is critical to keep services running and protect sensitive data. Come learn about the latest innovations from Google Cloud’s Cross-Cloud Network to protect workloads hosted in any cloud, on-premises, or colocation facility. Updates will cover Google Cloud Armor, reCAPTCHA Enterprise, Model Armor, and Apigee.

Companies in the fiercely competitive gaming landscape face constant pressure to create engaging and ever-evolving player experiences. Generative AI can help game developers craft more dynamic, personalized gameplay while reducing time to market. Major game studios are leveraging Google Cloud’s cutting-edge AI capabilities to create immersive player experiences, personalized chatbots, dynamic character interactions, and user-generated content. We’ll show you how you can use Google Kubernetes Engine to easily integrate gen AI with game servers.

This session dives into the practical application of generative AI and Google Cloud tools for transforming computer science education. Discover how educators can integrate these technologies into core computer science courses to equip future developers with the in-demand skills needed for an AI-driven future. We'll explore the Google Tech Exchange curriculum, a model for bridging the gap between academia and industry through hands-on experience with cutting-edge AI and cloud technologies.

Learn how Equifax is driving productivity gains by adopting Gemini & Google Workspace. We’ll cover their strategic migration from Microsoft to Workspace, which set the foundation for seamless generative AI. This session highlights their Gemini pilot for 1,000 users, focusing on practical strategies for change management & maximizing user adoption. We’ll share how Equifax empowered employees with prompt engineering & tailored use case training, offering a replicable model for organizations.

This Session is hosted by a Google Cloud Next Sponsor.
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PostgreSQL is one of the most popular open source databases for application development.  Furthermore, native support for vector search makes PostgreSQL an excellent choice for generative AI app development too. Learn why Google Cloud is the best place for your PostgreSQL workloads across Cloud SQL, AlloyDB and Spanner database offerings. Also hear from Salesloft about their journey to Google Cloud and how they chose which database service to select for their workloads.

The future of AI is at the edge and edge inferencing is transforming industries. The power of an AI-ready data center, connected to Google Cloud, optimizes edge AI by bringing AI processing closer to all types of data sources for unprecedented speed and efficiency, enabling real-time insights. Success relies on low latency and high-performance physical infrastructure; Equinix's global network of 260+ AI-ready data centers in 73 metros securely connects clouds to customers, partners, and service providers to accelerate AI deployments.

This Session is hosted by a Google Cloud Next Sponsor.
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AlloyDB for PostgreSQL is Google Cloud’s high-performance, PostgreSQL-compatible database service for your demanding online transaction processing (OLTP), hybrid transactional and analytical, and generative AI applications. In this session, we’ll cover what’s new with AlloyDB, including critical enterprise features across performance, availability, ease of use, and more. You’ll also learn how customers are quickly migrating to AlloyDB with Database Migration Service and how they’ve successfully scaled their workloads with AlloyDB, saving money while doing so.

In this session, we’ll build a functional generative AI application designed to solve a common IT challenge for small teams. We’ll start by defining a problem and exploring how gen AI can offer a solution. Next, we’ll select a pretrained model from Model Garden and use it to build a simple application with intelligent automation. Throughout the process, we’ll demonstrate testing and refinement techniques. This session is ideal for visual learners who want to see the power of gen AI in action and gain the confidence to build their own AI-powered solutions.

Join Deutsche Bank and Deloitte as we show you how our GenAI-powered chatbot is enhancing customer engagement, driving efficiency, and changing the face of banking. In this fascinating session, we'll demonstrate how the chatbot, integrated into the Deutsche Bank customer-facing banking app, provides accurate product and service information, guides customers to the right transactions, and seamlessly connects to live agents as needed. We'll also review insights and best practices for implementing your own chatbot solutions on Google Cloud.

This Session is hosted by a Google Cloud Next Sponsor.
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Imagine a world where interacting with your data is as simple as chatting with a friend. Gemini in Looker makes this a reality, bringing the power of Google's most advanced AI models and agents directly to your BI workflows. This session explores how Gemini's genAI capabilities and Looker Agents are being integrated into Looker, empowering users to analyze data, build dashboards, and generate insights using natural language. Discover how this powerful combination unlocks new levels of productivity for BI professionals and business users alike.

This hands-on lab guides you through building a captivating generative AI application using the Gemini API in Vertex AI. You'll leverage the Streamlit framework to create an interactive interface for generating stories, providing a seamless user experience. After testing your application locally in Cloud Shell, you'll deploy it to Cloud Run for scalable and reliable serving. This hands-on experience equips you with the skills to integrate Gemini with user interfaces and efficiently deploy your AI applications.

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!

Unlock the power of generative AI and data. Join experts from LlamaIndex and Google Cloud databases and learn how to seamlessly integrate LlamaIndex with AlloyDB and Cloud SQL for PostgreSQL, enabling your apps to reason, act on your data, and leverage the performance of Google Cloud. We’ll share real-world examples and code. Discover new possibilities for building advanced gen AI applications.

This session provides strategies for maximizing business value with generative AI. We cut through the hype and offer actionable insights for building and deploying advanced gen AI business capabilities. We'll delve into strategies that our customers use to get the most out of their AI investment, explore the essential foundations for scaling up, and share a vision for the future of business operations transformed by agentic AI.

As the number of distributed and generative AI applications grows in your organization, so will the number of APIs – presenting management and governance challenges. This session introduces API Hub, a solution for unified API management. Learn how to gain centralized observability over your APIs, use the API Hub on-ramp framework to connect to any API gateway, help developers access shared components and standards to build compliant APIs faster, and discover and manage shadow APIs.

Creating a business case to modernize technology has always been challenging. Hear how McKinsey is using a multi agent architecture to automate complex software development flows efficiently and cost-effectively. See how gen AI agent squads are foundational for scaling workforce talent and enhancing organizational capabilities. Learn best practices and see real-world examples of how organizations are using a multi-agent gen AI approach to achieve faster, cheaper, and better results.

This Session is hosted by a Google Cloud Next Sponsor.
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AI is revolutionizing enterprise operations by transforming unstructured data into actionable intelligence, reducing manual effort, & converting data into powerful drivers of smarter, more connected operations. Explore the dynamic interplay of AI agents, collaborating seamlessly to orchestrate specialized tasks in real-time. Learn how connected intelligence breaks down silos, integrating data & systems to drive proactive, efficient operations. See this shift in action with Leah to learn how you can apply these best practices in your industry.

This Session is hosted by a Google Cloud Next Sponsor.
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This talk delves into the difficulties of managing AI costs, emphasizing cost estimation across various model deployments (closed foundation models, non-cloud provider APIs, and local models). Key areas of focus include strategies for projecting AI spend at both the workload and enterprise level, implementing cost showback mechanisms, optimizing AI spending, and developing business plans and forecasts using ML and GenAI.

This workshop examines the critical lessons learned in deploying generative AI applications and explores how these insights can shape the future of the "AI Agents era." We'll delve into the practical challenges and solutions encountered in moving from initial answers to actionable implementations, prescribing how these learnings can be applied to build more sophisticated, autonomous, and impactful AI systems.

Production-ready apps, including GenAI apps, demand robust telemetry. Explore the full lifecycle: from data generation to consumption. See how OpenTelemetry, scaled by BindPlane, delivers enterprise-grade observability within Google Cloud. Learn to centralize data, cut costs, and achieve proven customer success!

Are you a data scientist or developer using Python to build AI models and generative AI applications? Learn how BigQuery can supercharge Python data science workflows with capabilities that give you the productivity of Python and allow BigQuery to handle core processing. Offloading Python processing enables large-scale data analysis and seamless production deployments along the data-to-AI journey. Find out how Deutsche Telekom modernized their machine learning platform with a radically simplified infrastructure and increased developer productivity.

Commerzbank, the largest bank in Germany, is using Gemini to transform its financial advisory workflows. The company is seeing significant reductions in processing time of client documentation and increases in productivity with Vertex AI. Learn how Gemini's ability to understand multiple modalities and process long documentation along with the generative AI evaluation service on Vertex AI, played a key role in streamlining operations and enhancing the client experience.

Java developers, join us to connect with your peers and explore best practices for building robust GenAI Java applications. We'll walk through sample apps as we discuss topics including cost reduction, efficient embedding generation, entity management, and testing. Then we'll dive deeper into the topics most relevant to you.