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.

Discover how to integrate AI and Gen AI capabilities to unblock data quality issues, streamline the deployment processes of a data platform, and empower data teams to accelerate the development of customized data products. By automating data product and pipeline creation, infrastructure deployment, data quality, and PII controls, you can reduce engineering efforts by 30-40% and develop products three times faster. Learn how this approach has helped clients create data products faster and more cost-efficiently across various industries.

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.

Explore the future of data management with BigQuery multimodal tables. Discover how to integrate structured and unstructured data (such as text, images, and video) into a single table with full data manipulation language (DML) support. This session demonstrates how unified tables unlock the potential of unstructured data through easy extraction and merging, simplify Vertex AI integration for downstream workflows, and enable unified data discovery with search across all data.

The next generation of intelligent business applications is here and powered by generative AI. In this session, you will learn about Spanner's latest graph capabilities and how GraphRAG can help you deliver richer contextual generative AI applications. Discover how to leverage a consolidated data platform to create smarter, more intuitive applications and drive business innovation.

Cloud, AI, and data analytics technologies have the potential to revolutionize healthcare - streamlining eligibility determination, automating administrative processes, and providing greater access to critical services. By tailoring interventions, resources, and communication strategies to individual needs, technology can enable more effective, engaging, and personalized care for all.

Model Armor is designed to protect your organization’s AI applications from security and safety risks. In this session, we’ll explore how Model Armor acts as a crucial layer of defense, screening both prompts and responses to identify and mitigate threats such as prompt injections, sensitive data leakage, and offensive content. Whether you’re a developer looking to implement AI safety or a professional interested in better visibility into AI applications, Model Armor offers comprehensive yet flexible security across all of your large language model (LLM) applications.

Tensor Processing Units (TPUs) are a hardware accelerator designed by Google specifically for large-scale AI/ML computations. Google's new Trillium TPUs are our most performant and energy-efficient TPUs to date, and offer unprecedented levels of scalability. Ray is a unified framework for orchestrating AI/ML workloads on large compute clusters. Ray offers Python-native APIs for training, inference, tuning, reinforcement learning, and more. In this lightning talk, we will demonstrate how you can use Ray to manage workloads on TPUs with an easy-to-use API. We will cover: 1) Training your models with MaxText, 2) Tuning models with Huggingface, and 3) Serving models with vLLM. Audience can gain an understanding of how to build a complete, end-to-end AI/ML infrastructure with Ray and TPUs.

Leaders of small businesses from around the globe take the stage to discuss how they’re using generative AI to bring positive change to their communities and environment. In this panel, we’ll show you how there are no limits to what your business can create.

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.

Balancing developer agility with security compliance is a key challenge in AI-driven, cloud-native development. Learn how Docker and Google Cloud integrate security into every phase of the software lifecycle—enabling teams to build, test, and deploy AI features and applications with confidence. Embed security in developer workflows, enhance supply chain integrity with SLSA provenance and SBOM attestations, and leverage trusted content on seamless workflows with Google Cloud.

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.

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**

AI applications that use the retrieval augmented generation (RAG) architecture can be a lot more accurate than those built with just the AI model’s built-in knowledge. But RAG introduces additional processing steps which need to be monitored. We’ll show you how.

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!

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!

Scale your AI training and achieve peak performance with AI Hypercomputer. Gain actionable insights into optimizing your AI workloads for maximum goodput. Learn how to leverage our robust infrastructure for diverse models, including dense, Mixture of Experts, and diffusion. Discover how to customize your workflows with custom kernels and developer tools, facilitating seamless interactive development. You'll learn firsthand how Pathways, developed by Google Deepmind, enables large scale training resiliency, flexibility to express architecture.

AI offers the opportunity to transform manufacturing. In this session, we’ll share Google Cloud’s perspective and specific use cases that can boost productivity and operational efficiency, including new research findings. The session features customers at the forefront of the AI revolution and the foundational pillars that manufacturers need to innovate at scale.

Unlock the power of natural language with Looker Agents! This technical deep dive will walk you through an agentic architecture in Looker Conversational Analytics and showcase how the Chief Product Officer of Zeotap is helping Zeotap customers “chat with their data” within the Zeotap platform using the new Conversational Analytics API. Learn how to build custom data agents, answer questions in Workspace, and create analytics applications with the power of conversational AI.

Join Virgin Media O2 and Google for a technical discussion about lessons learned and best practices for building and scaling a data fabric on BigQuery. Find out how Virgin Media O2 eliminated silos and enabled secure and governed data sharing at scale to drive better decisions and get more value from their data.

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.