Running AI workloads on Google Kubernetes Engine (GKE) presents unique challenges, especially for securing the right hardware. Whether you’re dealing with unpredictable demand and varying job durations or simply looking to control costs, this session will equip you with the knowledge and tools to make informed decisions about your GKE AI infrastructure. We’ll explore recent advancements in Dynamic Workload Scheduler, custom compute classes, and Kueue, demonstrating how these technologies can help you effectively access and manage diverse hardware resources.

Experience the power of AlloyDB Omni, a cutting-edge PostgreSQL-compatible database designed for multicloud and hybrid cloud environments. This session explores how AlloyDB Omni accelerates the development of modern applications, enabling generative AI experiences, efficient vector search, real-time operational analytics, and scalable transactional performance. We’ll also showcase how to run your applications on multiple clouds using Aiven’s seamless managed service, and how to supercharge hybrid cloud deployments with cloud-ready partners.

Unleash the full potential of large language models (LLMs) on your edge devices, even when there’s spotty internet. This session explores a hybrid approach that combines the power of cloud-based LLMs with the efficiency of on-device models. Learn how to intelligently route queries, enabling laptops and mobile phones to perform complex tasks while maintaining snappy performance. View demos of efficient task routing that optimizes for quality and cost to ensure your apps run smoothly, even during network disruptions.

Discover how Google Distributed Cloud empowers partners to deliver AI solutions for edge and on-premises environments. Learn how the GDC Partner Initiative can help you drive innovation with customers, expand service offerings, and grow revenue. Hear directly from one of our pioneering partners about their journey leveraging GDC to capitalize on market demand while creating new business opportunities in a rapidly evolving market.

The open-source AI agent landscape is thriving with innovation. This session is your definitive guide to building, deploying, and monitoring OSS agent frameworks. Learn patterns and best practices that combine the best of open-source frameworks with the AI platform built for production – Vertex AI. In this session, we'll cover techniques for multi-agent orchestration, working with diverse data sources, and building autonomous workflows. Join us on a journey from open-source agent frameworks to production-grade agent deployments and LLMOps on Vertex AI.

Dive deep into how governance, security, and sharing are innately integrated in BigQuery to power data and AI use cases across your organization. Learn about new innovations that further enhance data governance, security, and collaboration across data and AI assets, without you having to leave BigQuery. Find out how data governance leaders at Walmart and Box are using BigQuery to securely scale data and AI across their organizations.

Are you a site reliability engineer (SRE) for an organization running generative AI workloads? If gen AI is transforming your workloads, are your SRE skills keeping pace? This session is a must for SREs facing the unique challenges of gen AI. Learn to adapt the four golden signals – tackling latency in multistage pipelines, user satisfaction in nondeterministic systems, and new error types like hallucinations. Discover how Google Cloud Observability and Firebase Genkit AI monitoring can help you master gen AI SRE.

Grappling with scaling your AI and machine learning (ML) platforms to meet demand and ensuring rapid recovery from failures? This session dives into strategies for optimizing end-to-end startup latency for AI and ML workloads on Google Kubernetes Engine (GKE). We’ll explore how image and pod preloading techniques can significantly reduce startup times, enabling faster scaling and improved reliability. Real-world examples will show how this has led to dramatic improvements in application performance, including a 95% reduction in pod startup time and 1.2x–2x speedup.

Many organizations are scrambling to adopt Aritificial Intelligence tools across their teams, and like any new technology rollout, they are encountering challenges- both expected and unexpected. CME Group recently rolled out Gemini Code Assist to one of their large software development organizations and are excited to share takeaways around people, process, and tools. The topics include: compliance and information security considerations, 
managing rollout and adoption: starting small and scaling, and how these tools can help reshape the workday of your teams. No matter where you are in your AI adoption journey, you're sure to learn something new!

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!

Discover how Snap and Google Cloud are redefining AI-powered engagement through cross-team collaboration with Google. This session will teach you how Snapchat leverages Google to enable their growth and platform advancement.  Gain insights into Snap’s holistic journey, the impact of a tailored Google approach and engagement model, and strategies for startups to integrate Google’s solutions to enable the growth of your platform.

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.

This hands-on lab introduces Gemini 2.0 Flash, the powerful new multimodal AI model from Google DeepMind, available through the Gemini API in Vertex AI. You'll explore its significantly improved speed, performance, and quality while learning to leverage its capabilities for tasks like text and code generation, multimodal data processing, and function calling. The lab also covers advanced features such as asynchronous methods, system instructions, controlled generation, safety settings, grounding with Google Search, and token counting.

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!

Hear how the revolutionary strategies and cutting-edge technologies are transforming organizations to navigate an unpredictable cybersecurity landscape. Discover how emerging trends and innovative solutions are shaping the way we protect our digital assets. Learn more about the latest advancements in borderless IT, Zero Trust, multi-cloud environments, and AI-driven security. It’s an engaging and insightful journey into the latest in cybersecurity.

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.

This talk explores a solution for the analysis of medical images, with the goal of identifying subtle indicators of cancer. The solution encompasses the ingestion, analysis, annotation, and storage of medical images to facilitate the detection of cancerous cells and enable further insights. Additionally, the solution supports the development of AI diagnostic models by converting images and metadata into formats conducive to machine learning, such as embeddings.

Our customer had been using Spanner for relational data and Tiger Graph for graph data, which prevented them from cross-referencing the two and created additional processing overhead. To address this, Google migrated the customer’s graph datasets into Spanner GraphDB. This involved creating TDD, scripts, and tools for graph schema transformations and loading data into the graph DB. Google also developed the long-awaited Corporate graph hierarchy for the customer and assisted with multiple graph query use cases essential to their business.

Discover how Vertex Search Commerce revolutionizes e-commerce by delivering world-class, personalized experiences that truly delight customers. Learn how strategic migration to this intelligent search engine, focusing on robust data pipelines and embracing AI-powered ranking, can significantly reduce zero-result searches and dynamically showcase trending items. This talk delves into the critical role of A/B testing in objectively measuring the transformative power of Vertex Search. We'll explore how rigorous experimentation allows us to not only measure the positive impact but also to identify and rectify any underlying configuration issues. Discover how a data-driven approach through meticulous A/B testing ensures Vertex Search is at peak performance, enabling you to fine-tune your implementation and be at the forefront of AI-powered product discovery landscape.

This session explores building sensitive data protection directly into Retrieval-Augmented Generation (RAG) architectures. We'll demonstrate how to leverage Cloud Data Loss Prevention (Cloud DLP) and the Faker Library to anonymize sensitive data within the RAG pipeline. The session will cover techniques for reversible transformations using Memorystore and Firestore for data mapping, and discuss integrating these methods with Large Language Models (LLMs) like Gemini via LangChain and Vertex AI Search. Learn how to create secure and compliant AI solutions that protect sensitive data and adhere to regulations like the EU AI Act.

Abstract - AI is revolutionizing the underwriting process in the insurance industry. This session will explore how AI-driven models can streamline risk assessment, enhance decision-making, and improve customer experiences. We'll discuss the benefits of AI in underwriting, along with the challenges and ethical considerations of implementation. Attendees will gain insights into the latest AI tools and best practices for integrating AI into their underwriting workflows, driving efficiency and accuracy in risk management.

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.

What if building an AI agent that thinks, reasons, and acts autonomously took less time than your coffee break? With Vertex AI, it’s not just possible. It’s easy. Join DoiT to see how to build, deploy, and scale a production-ready AI agent in 10 minutes using Google’s top services: Gemini 2 for language understanding, the RAG Engine for fetching information, and the Agent Engine for orchestration. To top it off, watch a live demo take an agent from concept to production-ready in real time.

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.