Episode 5 of 5 covering multi-agent systems and the A2A protocol.

AI-powered Data Engineering Agents usher in a new era of data agility. Engage with Google Cloud and your peers to explore the implementation of autonomous data agents and their impact on enterprise agility. From automating data pipelines to ingestion to transformation, discover how to leverage autonomous data agents to build self-managing data ecosystems and accelerate the time from raw data to impactful decisions. This is where data's potential truly meets AI power.

Accelerating AI use cases demands strong data governance and many organizations struggle to manage complex, growing data volumes effectively. This session explores essential strategies for building a solid data governance foundation. Learn how organizations are overcoming common data governance obstacles, like data silos and inconsistent rules, to achieve measurable gains in data quality and efficiency. Through real-world examples, discover how unified data platforms can simplify data discovery, classification, and policy enforcement, leading to faster, data-driven decisions and reduced risk.

AI's potential depends on quality data. Many struggle with AI due to data governance or slow processes, especially with unstructured data. Join peers in discussing strategies for improving and governance to maximise AI potential, managing structured and unstructured data, connecting LLMs with enterprise data and data security best practices.

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.

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.

Bring your laptop and join us for an interactive demo on how to apply large language models (LLMs) from the Vertex AI Model Garden to a business use case, and learn about best practices for monitoring these models in production. We’ll go through an exercise using Colab Enterprise notebooks and learn how to use out-of-the-box tools to monitor RED (rate, error, duration) metrics, configure alerts, and monitor the rate of successful predictions in order to ensure successful use of a Vertex AI model in production.

This panel explores the potential of cloud technologies for operational technology (OT) and the critical need for proactive cybersecurity measures. The convergence of OT and IT, driven by cloud adoption, presents both opportunities and challenges. Panelists will examine the benefits of cloud-based OT, such as increased efficiency, scalability, data-driven insights, and resilience, along with the opportunity to build with security in mind.

Firestore with MongoDB compatibility is a serverless database service  designed to maximize scalability, high availability and performance without the hidden costs of capacity planning. This session demonstrates the new Firestore with MongoDB compatibility capabilities and discusses how Dialpad has built an Ai-powered customer communications platform leveraging Firestore over the last 14 years to grow a successful, performant, reliable business.

Learn how to manage security controls and licenses for thousands of users, and tie it all together with APIs. We’ll show you ways to manage developer access more efficiently, build custom management integrations, and keep your CISO happy at the same time. We’ll also demo the new Gemini Code Assist integration with Apigee, which lets developers use Gemini Code Assist chat to generate context-aware OpenAPI specifications that reuse components from other APIs in their organization for efficiency and reference organizational security standards.

Join this session to learn best practices for optimizing your data and analytics costs. Discover new BigQuery capabilities that simplify workload management and provide greater cost controls and adherence to best practices. BigQuery customers Just Eat Takeaway and Trendyol will share their BigQuery migration journeys, scaling strategies, and how they used workload management and optimization tools to improve their return on investment (ROI).

Join us for an in-depth session on Firebase Genkit, an open source framework that simplifies the development of AI-powered applications. Discover how to use the Node.js and Go SDKs to build intelligent chatbots, multimodal content generators, streamlined automation workflows, and agentive experiences. We'll demonstrate how Genkit's unified interface seamlessly integrates Google's Gemini and Imagen models, self-hosted Ollama options, and a variety of popular models from Vertex AI Model Garden. 

Migrating from AWS or Azure to Google Cloud runtimes can feel like navigating a maze of complex services and dependencies. In this session, we’ll explore key considerations for migrating legacy applications, emphasizing the “why not modernize?” approach with a practice guide. We’ll share real-world examples of successful transformations. And we’ll go beyond theory with a live product demo that showcases migration tools, and a code assessment demo powered by Gemini that demonstrates how you can understand and modernize legacy code.

JavaScript gets a lot of flak for not being strongly typed. But if you’re running JavaScript in production today, you don’t need to wait for runtime errors to catch problems. TypeScript has taken JavaScript from a loosely typed language, where a variable can change from a string to a number without warning, and made it strongly typed. Now Zod and Effect are here to tame even the wildest unknown parameters from your users. We’ll demonstrate using these tools in an application and we’ll deploy that application to Google Cloud.

Learn how to leverage Google Cloud’s innovations to build the most secure and compliant solutions with Confidential Computing, offloads, and Assured Workload capabilities.

Simplify real-time data analytics and build event-driven, AI-powered applications using BigQuery and Pub/Sub. Learn to ingest and process massive streaming data from users, devices, and microservices for immediate insights and rapid action. Explore BigQuery's continuous queries for real-time analytics and ML model training. Discover how Flipkart, India’s leading e-commerce platform, leverages Google Cloud to build scalable, efficient real-time data pipelines and AI/ML solutions, and gain insights on driving business value through real–time data.

Cloud marketplaces are projected to reach $85B by 2028, with over half involving channel partners (Source: Canalys). Google Cloud Marketplace offers a unique advantage for Channel Partners and ISVs to collaborate and succeed. Learn about the latest platform capabilities to drive deal velocity, new resell offerings and incentives designed to scale growth. Tap into new revenue through the channel and thrive in the evolving cloud marketplace.

In today’s global media landscape, localizing video content is key to reaching wider audiences. This session demonstrates how to build a robust, end-to-end AI video dubbing pipeline on Google Cloud—covering video ingestion, transcription, translation, captioning, voice cloning, voice synthesis, and quality checks. We’ll explore an architecture that seamlessly integrates GCP products and best practices, highlight market opportunities, and address key challenges in AI dubbing. Attendees will learn how to streamline workflows so users can simply submit their video and receive fully dubbed results. Join us to see how Google tackles dubbing hurdles to maintain its leading edge in global content localization.

Unlock your team's full potential with the power of Google Cloud training for partners. Explore the learning portfolio designed for partner practicioners including role-based learning paths, certification programs, skill badges, and more. Plus, we'll highlight the latest from the generative AI portfolio. Boost capabilities and drive customer success without compromising productivity!

As AI adoption accelerates, many enterprises still face challenges building production-grade AI systems for high-value, knowledge-intensive use cases. RAG 2.0 is Contextual AI’s unique approach for solving mission-critical AI use cases, where accuracy requirements are high and there is a low tolerance for error. 

In this talk, Douwe Kiela—CEO of Contextual AI and co-inventor of RAG—will share lessons learned from deploying enterprise AI systems at scale. He will shed light on how RAG 2.0 differs from classic RAG, the common pitfalls and limitations while moving into production, and why AI practitioners would benefit from focusing less on individual model components and more on the systems-level perspective. You will also learn how Google Cloud’s flexible, reliable, and performant AI infrastructure enabled Contextual AI to build and operate their end-to-end platform.

Tired of generic code suggestions? Learn how to customize Gemini Code Assist using your source code repositories. This session covers best practices for generating new code, and retrieving and reusing existing code, with Gemini Code Assist code-customization capabilities. Boost productivity, enforce consistency, and reduce cognitive load with a truly personalized AI coding assistant.

Unlock the power of generative AI with retrieval augmented generation (RAG) on Google Cloud. In this session, we’ll navigate key architectural decisions to deploy and run RAG apps: from model and app hosting to data ingestion and vector store choice. We’ll cover reference architecture options – from an easy-to-deploy approach with Vertex AI RAG Engine, to a fully managed solution on Vertex AI, to a flexible DIY topology with Google Kubernetes Engine and open source tools – and compare trade-offs between operational simplicity and granular control.

Explore how distributed cloud solutions solve for computing in sensitive on-premises, harsh, and remote environments with stringent regulatory and sovereignty requirements. Learn how these solutions enable secure access to advanced cloud capabilities like data analytics and AI within completely isolated environments, ensuring strict compliance and data residency. Key implementation and management considerations will be discussed.

Discover how some of the world’s most innovative companies modernized and transformed their applications with the power of Firestore, Firebase, and cutting-edge generative AI. Learn how they leveraged the latest technologies, such as edge computing and AI, to enhance customer experiences at every stage of the customer journey. Explore their innovative architecture and gain insights into building modern, engaging applications that deliver exceptional customer experiences.

This session explores the evolution of data management on Kubernetes for AI and machine learning (ML) workloads and modern databases, including Google’s leadership in this space. We’ll discuss key challenges and solutions, including persistent storage with solutions like checkpointing and Cloud Storage FUSE, and accelerating data access with caching. Customers Qdrant and Codeway will share how they’ve successfully leveraged these technologies to improve their AI, ML, and database performance on Google Kubernetes Engine (GKE).