Generative AI and machine learning (ML) are transforming industries, but many smaller organizations believe these technologies are out of reach due to limited resources and specialized skills. In this session, we’ll demonstrate how BigQuery is changing the game, making gen AI and ML accessible to teams of all sizes. Learn how BigQuery – with its serverless architecture, built-in ML capabilities, and integration with Vertex AI – empowers smaller teams to unlock the power of AI, drive innovation, and gain a competitive edge.

Organizations are racing to deploy generative AI solutions built on large language models (LLMs), but struggle with management, security, and scalability. Apigee is here to help. Join us to discover how the latest Apigee updates enable you to manage and scale gen AI at the enterprise level. Learn from Google’s own experience and our work with leading customers to address the challenges of productionizing gen AI.

Unlock the power of lightning-fast vector search for your generative AI applications. This session dives deep into Memorystore vector search, demonstrating how to achieve single-digit millisecond latency on over a billion vectors. Explore cutting-edge gen AI application architectures that leverage vector search and other Google Cloud services to deliver exceptional user experiences.

Join an insightful fireside chat with Jeff Dean, a pioneering force behind Google’s AI leadership. As Google's Chief Scientist at DeepMind & Research, Jeff will share his vision on AI and specialized AI hardware, including Cloud TPUs seventh generation chip; Ironwood. What exciting things might we expect this to power? What drives Google’s innovation in specialized AI hardware? In this spotlight, we’ll also discuss how TPUs enable efficient large-scale training and optimal inference workloads including exclusive, never-before-revealed details of Ironwood, differentiated chip designs, data center infrastructure, and software stack co-designs that makes Google Cloud TPUs the most compelling choice for AI workloads.

Discover real-world examples of how generative AI is delivering tangible success across key industries – and where this technology is headed next. Hear from two experienced Google Cloud partners, EPAM and Persistent, as they share their experiences of harnessing the broad power of gen AI to solve niche challenges within traditional organizations.

In-person Closing Keynote exploring the evolving role of developers in the age of AI.

Explore how startups are creating impact for a wider range of users. Discover real-world examples of AI transforming hiring practices, product design, and user interfaces, and join the discussion on creating AI that serves everyone.

AI is revolutionizing observability. Learn about Cloud SQL AI-powered Database Insights and how it can help you optimize your queries and boost database performance. We’ll dive deep into the new Insights capabilities for MySQL, PostgreSQL, and SQL Server, including the Gemini-powered chat agent. Learn how to troubleshoot those tricky database performance issues and get practical tips to improve the performance of your applications.

The rise of AI demands an easier and more efficient approach to data management. Discover how small IT teams are transforming their data foundations with BigQuery to support AI-powered use cases across all data types – from structured data to unstructured data like images and text (multimodal). Learn from peers across industries and geographies why they migrated to BigQuery and how it helped them accelerate time to insights, reduce data management complexity, and unlock the full potential of AI.

Build more capable and reliable AI systems by combining context-aware retrieval-augmented generation (RAG) with agentic decision-making in an enterprise AI platform, all in Java! This session covers everything from architecture, context construction, and model routing to action planning, dynamic retrieval, and recursive reasoning, as well as the implementation of essential guardrails and monitoring systems for safe deployments. Learn about best practices, trade-offs, performance, and advanced techniques like evaluations and model context protocol.

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.

Generative AI agents have emerged as the leading architecture for implementing complex application functionality. Tools are the way that agents access the data and systems they need. But building and deploying tools at scale brings new challenges. Learn how MCP Toolbox for Databases, an open source server for gen AI tool management, enables platforms like LangGraph and Vertex AI to easily connect to enterprise databases.

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.

AI-enabled browser agents are in the news now, but it’s not always clear how they solve real-world problems. In this session, we’ll share our experience building a web browser agent by integrating Gemini into an end-to-end service that follows text instructions to take actions in a web application. We’ll take you through our journey of creating the agent, share the research that inspired us, and show how we’ve used the system to tackle practical problems like validating user flows in the UI and semantically checking web links.

This talk demonstrates a fashion app that leverages the power of AlloyDB, Google Cloud’s fully managed PostgreSQL-compatible database, to provide users with intelligent recommendations for matching outfits. User-uploaded data of their clothes triggers a styling insight on how to pair the outfit with matching real-time fashion advice. This is enabled through an intuitive contextual search (vector search) powered by AlloyDB and Google’s ScaNN index to deliver faster vector search results, low-latency querying, and response times. While we’re at it, we’ll showcase the power of the AlloyDB columnar engine on joins required by the application to generate style recommendations. To complete the experience, we’ll engage the Vertex AI Gemini API package from Spring and LangChain4j integrations for generative recommendations and a visual representation of the personalized style. This entire application is built on a Java Spring Boot framework and deployed serverlessly on Cloud Run, ensuring scalability and cost efficiency. This talk explores how these technologies work together to create a dynamic and engaging fashion experience.

Join Woosuk Kwon, Founder of vLLM, Robert Shaw, Director of Engineering at Red Hat, and Brittany Rockwell, Product Manager for vLLM on TPU, to learn about how vLLM is helping Google Cloud customers serve state-of-the-art models with high performance and ease of use across TPUs and GPUs.

Join us as we explore the intersection of computer use capabilities and the broader challenge of building effective AI agents. We'll examine how these developments map to the core requirements of AI agents: the ability to plan through strong reasoning and contextual understanding, act via direct computer interaction and tool use, and reflect through learning from experience. We'll share insights from recent implementations, and explore how emerging capabilities in areas like computer use are shaping the development of more capable AI systems.

This Session is hosted by a Google Cloud Next Sponsor.
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Discover the power of Google Cloud instances running on the latest Intel Xeon processors. This course will introduce you to Intel’s optimization tools, designed to help you manage and optimize your infrastructure with unmatched efficiency and performance. Learn how to leverage these cutting-edge technologies to enhance your cloud computing capabilities and drive your business forward.​

This Session is hosted by a Google Cloud Next Sponsor.
Visit your registration profile at g.co/cloudnext to opt out of sharing your contact information with the sponsor hosting this session.

Move your generative AI projects from proof of concept to production. In this interactive session, you’ll learn how to automate key AI lifecycle processes—evaluation, serving, and RAG—to accelerate your real-world impact. Get hands-on advice from innovative startups and gain practical strategies for streamlining workflows and boosting performance.

Learn how LG AI Research uses Google Cloud AI Hypercomputer to build their EXAONE family of LLMs and innovative Agentic AI experiences based the models. EXAONE 3.5, class of bilingual models that can learn and understand both Korean and English, recorded world-class performance in Korean. The collaboration between LG AI Research and Google Cloud enabled LG to significantly enhance model performance, reduce inference time, and improve resource efficiency through Google Cloud's easy-to-use scalable infrastructure