Discover how Google Cloud's application integration solutions create seamless customer journeys, enhance personalization, and optimize retail search using real-time data. We'll explore how retailers leverage customer insights to boost revenue, drive engagement, and deliver exceptional experiences. Empower your retail business to attract and retain customers, ultimately exceeding their expectations and driving bottom-line growth.

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Learn more about the new Google Meet API and SDKs that let you build integrated workflows with Meet and bring shared experiences with your app right inside the meeting. With our latest API, developers can build workflows using critical data from meetings like participants, transcripts, recording, and more. We’ll also share how you can bring Meet inside your app and give you a glimpse of what's coming up for our platform. No matter where users are, developers can extend the power of Google Meet to keep users connected, collaborating, and engaged.

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Ori Goshen, Co-Founder and Co-CEO of AI21 Labs, is a seasoned entrepreneur who previously co-founded Crowdx and developed the first-ever Voice over Internet Protocol and messaging app for iPhone and Android.

Get his unique perspective on the emergence of small, specialized models in the generative AI space and how building a strong partnership with Google Cloud was integral to their trajectory. AI21 Labs continues to innovate by building reliable, practical, and scalable AI systems for enterprises to accelerate the use of AI in production.

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Learn how the DoD is using AI at the edge to improve cancer detection for service members and veterans. The Augmented Reality Microscope (ARM) is deployed at remote military treatment facilities around the world. The prototype device is helping pathologists find cancer faster and with better accuracy.

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Build AI-powered workflows and app integrations with Google Workspace. We’ll share our vision for Gemini-powered workflows that are seamlessly integrated across our Workspace apps – built in a way that the users hardly notice it’s a workflow they are creating. We’ll also cover the latest news on Google Workspaces platform and ecosystem capabilities in Google Meet, Google Chat apps, and Smart Canvas. Also, we’ll share the latest integration news for Gemini for Google Workspace, including Salesforce and a new partnership.

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Firewalls are essential for any network security architecture. As organizations embrace the cloud, they seek cloud-first firewall solutions that seamlessly adapt to their evolving workload protection requirements. This session explores how you can reach this goal with Google Cloud's next generation firewall (NGFW). Learn how to secure all network paths with advanced threat prevention, coupled with flexible and granular control to ensure a strong security posture in Google Cloud. Plus, you'll gain insights from shared customer experiences in safeguarding workloads with Cloud NGFW.

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Sophisticated fraud is a growing problem: Learn how Google Cloud can help. We’ll show how using reCAPTCHA Enterprise and Web Risk, sites of all sizes can protect themselves against credential theft, financial fraud, phishing and scams. Reddit's Safety team will share how it successfully applied these tools to make Reddit a safer environment for users.

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The key to maintaining a strong cloud security posture is to build from the start on a robust foundation of baseline security controls. Google Cloud’s Security Foundation provides recommended controls to common cloud adoption use cases, including infrastructure modernization, AI workloads, data analytics, and application modernization. In this session, you’ll learn how to start secure and stay secure in the cloud using the Security Foundation.

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Learn how you can quickly and easily build applications in environments with predefined controls and guardrails to meet global regulatory compliance requirements. In this session, you’ll hear what's new in Assured Workloads and all the latest capabilities that will help you to easily achieve your data residency and compliance goals.

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In this game you will create and manage permissions for Google Cloud resources, run structured queries on BigQuery and Cloud SQL, create several VPC networks and VM instances and test connectivity across networks, and monitor a Google Compute Engine VM instance with Cloud Monitoring.

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Join us on Uber's journey to revolutionizing its data platform through Google Cloud. Discover how this migration has enhanced reliability, scalability, and analytics capabilities, showcasing the transformative power of Google Cloud in the ride-sharing industry. Join us for this Mini Talk at 'Meet the Experts, hosted by Google Cloud Consulting' at Expo. Seating is limited and on a first-come, first served basis; standing areas are available.

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In this mini course you will be introduced to Vertex AI, and will explore the three key phases of the machine learning workflow in Vertex AI—data preparation, model training, and model deployment - and how different products in Vertex AI can support you during each phase. At the end of the course, you will be able to practice building a machine learning model with AutoML in a live lab environment.

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In this mini course you will learn how to optimize performance and cost in BigQuery. You will learn how to optimize your queries and lower cost by optimizing your storage using partitioning and clustering. You will explore these techniques in a hands-on lab environment by exploring data inspired by a real customer use case.

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Training large AI models at scale requires high-performance and purpose-built infrastructure. This session will guide you through the key considerations for choosing tensor processing units (TPUs) and graphics processing unit (GPUs) for your training needs. Explore the strengths of each accelerator for various workloads, like large language models and generative AI models. Discover best practices for training and optimizing your training workflow on Google Cloud using TPUs and GPUs. Understand the performance and cost implications, along with cost-optimization strategies at scale.

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In this session, you'll learn how the platform team can provide a multi-tenant traffic-management infrastructure to optimize performance, route efficiently to reduce costs, and simplify operations. We'll demonstrate how multi-cluster service and multi-cluster Gateway can be used to abstract the cloud infrastructure and how Google Kubernetes Engine (GKE) Enterprise can empower the platform team managing fleets of GKE clusters and teams consuming those clusters.

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Generative AI has the potential to transform the way we live, work, bank, and invest. In this session, we will share Google Cloud's perspective and specific use cases that can boost productivity and operational efficiency in banking. The session will also feature customer success stories and a discussion with banking executives at the forefront of using generative AI.

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Customers increasingly want to run multiple analytics and artificial intelligence (AI) use cases on a single copy of their data spanning lakes and warehouses. However, the fragmented nature of today’s analytics and AI systems poses limits with distributed data and metadata across different engines. Google Cloud now offers a unified storage and metadata experience. Learn how these new capabilities in BigQuery can help unify the data and data sharing across engines and how HCA Healthcare is using them within its data ecosystem.

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Text-to-image generative AI models such as the Stable Diffusion family of models are rapidly growing in popularity. In this session, we explain how to optimize every layer of your serving architecture – including TPU accelerators, orchestration, model server, and ML framework – to gain significant improvements in performance and cost effectiveness. We introduce many new innovations in Google Kubernetes Engine that improve the cost effectiveness of AI inference, and we provide a deep dive into MaxDiffusion, a brand new library for deploying scalable stable diffusion workloads on TPUs.

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In this session, you’ll learn how to deploy a fully-functional Retrieval-Augmented Generation (RAG) application to Google Cloud using open-source tools and models from Ray, HuggingFace, and LangChain. You’ll learn how to augment it with your own data using Ray on Google Kubernetes Engine (GKE) and Cloud SQL’s pgvector extension, deploy any model from HuggingFace to GKE, and rapidly develop your LangChain application on Cloud Run. After the session, you’ll be able to deploy your own RAG application and customize it to your needs.

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HSBC has a large number of legacy IBM WebSphere applications that are costly to maintain and pose a compliance risk. This session will discuss how HSBC built a “migration factory” to help developers platform existing Websphere applications to Google Kubernetes Engine (GKE). The benefits of migrating these existing applications to GKE include reduced operational costs, improved compliance, increased scalability, faster application development, and improved security. Come learn exactly how HSBC did it and how you can replicate their process and success.

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Learn how platform engineering can provide multi-tenant traffic management to optimize performance, route efficiently to reduce costs, and simplify network operations. We‘ll demonstrate how multi-cluster services and multi-cluster gateways can be used to abstract the infrastructure for developers.

Learn from Shopify how they built their large-scale Kubernetes network to support 61 million shoppers and $9.3B in sales during Black Friday.

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Follow along as two Developer Relations Engineers work in real-time to develop a minimal viable Flutter app, backed by Firestore database through a Google Cloud Run-powered API. We'll see the Cloud Run developer experience, focusing on automation and error recovery to deploy a REST API. Based on this API, see how to develop a Flutter application showing the latest UI features.

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Stop juggling security tools and start focusing on your business: Discover how Deloitte Managed Cybersecurity Services seamlessly integrates Google Cloud Security and top security solutions to streamline your Security Operations. Slash security risks, cut costs, and get protected in under 60 days. Find out how this powerful combination can protect your business, both now and in the future with Gemini.

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Learn how to get the most out of your CI/CD tools through new features. Find out the latest product updates to create secure and reliable application repositories, builds, and deployments.

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Google AI and Vertex AI are two Google Cloud platforms that allow developers to access the Gemini API. In this session, developers will learn what is possible to do today, and they will see some sneak peeks about what is coming.

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