AI Hypercomputer is a revolutionary system designed to make implementing AI at scale easier and more efficient. In this session, we’ll explore the key benefits of AI Hypercomputer and how it simplifies complex AI infrastructure environments. Then, learn firsthand from industry leaders Shopify, Technology Innovation Institute, Moloco, and LG AI Research on how they leverage Google Cloud’s AI solutions to drive innovation and transform their businesses.

This demo shows AI network operations solutions that deliver advanced AI/ML powered tools and capabilities to understand impacts of network issues on telco customers, detect them, and resolve them faster through automated end-to-end correlation and root cause analysis. The solution leverages native GCP services

Learn how to transform production by connecting IT and OT data, powered by the latest releases of Manufacturing Data Engine and Cortex Framework with seamless integration. Ground your AI models with our data foundation and operate with integrated factory floor performance, machine and production insights.

Modernize your website and applications with Google’s specialized, AI-powered search products.

Build an AI-powered image detection game with Vertex AI in Firebase and Flutter. Begin to draw an object and watch Gemini analyze your doodle in real time and guess what you’re drawing. All in 20 seconds!

APIs dominate the web, accounting for the majority of all internet traffic. And more AI means more APIs, because they act as an important mechanism to move data into and out of AI applications, AI agents, and large language models (LLMs). So how can you make sure all of these APIs are secure? In this session, we’ll take you through OWASP’s top 10 API and LLM security risks, and show you how to mitigate these risks using Google Cloud’s security portfolio, including Apigee, Model Armor, Cloud Armor, Google Security Operations, and Security Command Center.

Build fully integrated streaming pipelines on Google Cloud and learn how to leverage AlloyDB, Datastream, BigQuery, Looker, and Vertex AI for real-time data analysis.

Did you know? You only need One API to Rule Them All! Google's Gen AI SDK provides a simple path to both the Gemini API and Vertex AI!

Play a game of pinball to learn about how Model Armor can protect your LLM app. Shoot shots to send prompts to Gemini, and watch as Model Armor detects and blocks prohibited prompts and responses.

Routine tasks such as data wrangling and pipeline maintenance often inhibit data teams from doing higher-value analysis and insights-led decision-making. This session showcases how intelligent data agents in BigQuery can help automate complex data engineering tasks. You’ll learn how to use natural language prompts to streamline data engineering tasks from ingestion and transformation, such as data cleaning, formatting, and loading results into BigQuery tables that accelerate the time to build and validate data pipelines.

Routine tasks such as data wrangling and pipeline maintenance often inhibit data teams from doing higher-value analysis and insights-led decision-making. This session showcases how intelligent data agents in BigQuery can help automate complex data engineering tasks. You’ll learn how to use natural language prompts to streamline data engineering tasks from ingestion and transformation, such as data cleaning, formatting, and loading results into BigQuery tables that accelerate the time to build and validate data pipelines.

Streamline data analytics workflows with AI assistance. Enhance data team productivity and reduce costs.

The Automotive AI Agent, powered by Gemini and Vertex AI, uses natural conversations to deliver intelligent responses and create next-generation vehicle experiences. The AI agent provides contextualized responses that keep up with your schedule and needs.

The first Google Axion virtual machine (VM), C4A, provides the best price performance for general purpose workloads in the industry, but don’t take it from us. We’ll share how Axion benchmarks for key workloads. Then, we’ll take a deeper look at leading customers using Google Axion VMs. They’ll discuss their use cases and how they architected their stack to run on Arm VMs, providing valuable tips for other customers considering a similar transition.

There are a lot of amazing AI features being announced at Google Cloud Next. In order to take full advantage of these, you need to make sure your data is being managed in a secure, centralized way. In this talk, you’ll learn how to set up your lakehouse to get your data ready for downstream workloads. You’ll view a demo involving an architecture of Google Cloud products that includes managing permissions on your data, configuring metadata management, and performing transformations using open source frameworks.

Go beyond the standard Google Workspace experience. Learn how to extend and integrate with the Workspace platform, and explore how Qodea and others have leveraged the Workspace platform to create custom solutions that have boosted efficiencies, driven productivity, and reduced user workloads.

This hands-on lab equips you with the practical skills to build and deploy a real-world AI-powered chat application leveraging the Gemini LLM APIs. You'll learn to containerize your application using Cloud Build, deploy it seamlessly to Cloud Run, and explore how to interact with the Gemini LLM to generate insightful responses. This hands-on experience will provide you with a solid foundation for developing engaging and interactive conversational 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!

This hands-on lab empowers you to build a cutting-edge multimodal question answering system using Google's Vertex AI and the powerful Gemini family of models. By constructing this system from the ground up, you'll gain a deep understanding of its inner workings and the advantages of incorporating visual information into Retrieval Augmented Generation (RAG). This hands-on experience equips you with the knowledge to customize and optimize your own multimodal question answering systems, unlocking new possibilities for knowledge discovery and reasoning.

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 AI! Build your own intelligent agent with hands-on guidance from Google Cloud Consulting's leading AI experts. No experience needed, just a desire to innovate and build into the future with AI!

Software development life cycle (SDLC) agents enable developers to build and run applications more effectively. See how they reduce toil for developers in tasks like safety testing and code documentation.

Learn to leverage the newest graph query capabilities to find hidden patterns, and build a Customer 360 graph for more personalized product recommendations.

Use agentic AI to unify diverse data sources – including Firestore, web searches, and API services – to create individualized experiences for each customer and help them purchase your products.

Join us to discuss serverless computing and event-driven architectures with Cloud Run functions. Learn a quick and secure way to connect services and build event-driven architectures with multiple trigger types (HTTP, Pub/Sub, and Eventarc). And get introduced to Eventarc Advanced, centralized access control to your events with support for cross-project delivery.

Build Google Workspace add-ons to simplify your work or integrate your platform with ours. Use Gemini to start building on Workspace today.

Build smart context systems with retrieval-augmented generation (RAG) pipelines, vector embeddings, or built-in search capabilities.