Join this session to discover how a phone plan selection app, built with Flutter and Firebase, leverages Gemini 2.0 to enhance and simplify the customer experience. Gain insights into the technical architecture, identify actionable strategies to implement similar AI-driven solutions in your own apps, and understand the key principles of using AI to enhance the customer experience.

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.

Language models have already evolved to do much more than language tasks, principally in the domain of image, audio, and soon video. Join Mostafa Dehghani to explore the emergent frontier of multimodal generation, what Gemini’s world knowledge unlocks that domain specific models cannot create, and how developers should be thinking about AI as a next-generation creative partner.

Join us for an insightful discussion with Understood.org, a leading nonprofit dedicated to supporting the 70 million Americans with learning and thinking differences, and discover how empowering neurodiverse employees with tools like Google Workspace and Gemini can foster a more productive workplace.

Unlock the power of lightning-fast vector search for your generative AI applications. This session dives deep into Memorystore vector search, demonstrating how to achieve single-digit millisecond latency on over a billion vectors. Explore cutting-edge gen AI application architectures that leverage vector search and other Google Cloud services to deliver exceptional user experiences.

Join an insightful fireside chat with Jeff Dean, a pioneering force behind Google’s AI leadership. As Google's Chief Scientist at DeepMind & Research, Jeff will share his vision on AI and specialized AI hardware, including Cloud TPUs seventh generation chip; Ironwood. What exciting things might we expect this to power? What drives Google’s innovation in specialized AI hardware? In this spotlight, we’ll also discuss how TPUs enable efficient large-scale training and optimal inference workloads including exclusive, never-before-revealed details of Ironwood, differentiated chip designs, data center infrastructure, and software stack co-designs that makes Google Cloud TPUs the most compelling choice for AI workloads.

Building and maintaining detection rules is the cornerstone of any high-performing security operations function, but it’s often easier said than done. Join us for an in-depth exploration of detections in Google Security Operations (Google SecOps) and learn how it empowers detection teams to stay ahead of threats – from curated detections delivered out of the box by Google SecOps to address the latest threats, to building custom rules using entity graphs, AI, and the wealth of functions and context provided by Google SecOps.

Discover real-world examples of how generative AI is delivering tangible success across key industries – and where this technology is headed next. Hear from two experienced Google Cloud partners, EPAM and Persistent, as they share their experiences of harnessing the broad power of gen AI to solve niche challenges within traditional organizations.

Learn how Database Migration Service can help you modernize your SQL Server databases to unleash the power of cloud databases and open source PostgreSQL! Convert your SQL Server schema and T-SQL code to PostgreSQL dialect with a click of a button in the DMS Conversion Workspace. Some objects could not be fully converted? Gemini can suggest a fix. Not yet familiar with PostgreSQL features? Ask Gemini to teach you how to convert SQL Server features to PostgreSQL equivalent ones. While Gemini is there - ask it to optimize the converted code or add some comments to explain the business logic. Once your database is fully converted and optimized you can migrate the data with minimal downtime using the change data capture powered migration job and complete your migration journey.

Explore how startups are creating impact for a wider range of users. Discover real-world examples of AI transforming hiring practices, product design, and user interfaces, and join the discussion on creating AI that serves everyone.

AI is revolutionizing observability. Learn about Cloud SQL AI-powered Database Insights and how it can help you optimize your queries and boost database performance. We’ll dive deep into the new Insights capabilities for MySQL, PostgreSQL, and SQL Server, including the Gemini-powered chat agent. Learn how to troubleshoot those tricky database performance issues and get practical tips to improve the performance of your applications.

The rise of AI demands an easier and more efficient approach to data management. Discover how small IT teams are transforming their data foundations with BigQuery to support AI-powered use cases across all data types – from structured data to unstructured data like images and text (multimodal). Learn from peers across industries and geographies why they migrated to BigQuery and how it helped them accelerate time to insights, reduce data management complexity, and unlock the full potential of AI.

Build more capable and reliable AI systems by combining context-aware retrieval-augmented generation (RAG) with agentic decision-making in an enterprise AI platform, all in Java! This session covers everything from architecture, context construction, and model routing to action planning, dynamic retrieval, and recursive reasoning, as well as the implementation of essential guardrails and monitoring systems for safe deployments. Learn about best practices, trade-offs, performance, and advanced techniques like evaluations and model context protocol.

Organizations are facing sophisticated and growing cyberthreats from commercially driven ransomware groups and state-sponsored adversaries that legacy productivity solutions struggle to defend against. Learn how Google’s multilayered approach – AI threat defenses, a reduced attack surface, and built-in security controls in Google Workspace, Chrome Enterprise, and ChromeOS – can effectively combat the most prevalent cyberthreats and block malicious actors from gaining access to your data and disrupting your business.

Audiences around the world have almost limitless access to content that’s only a click, swipe, or voice command away. Companies are embracing cloud capabilities to evolve from traditional media companies into media-tech and media-AI companies. Join us to discover how the cloud is maximizing personalization and monetization to enable the next generation of AI-powered streaming experiences for audiences everywhere.

Get the inside story of Yahoo’s data lake transformation. As a Hadoop pioneer, Yahoo’s move to Google Cloud is a significant shift in data strategy. Explore the business drivers behind this transformation, technical hurdles encountered, and strategic partnership with Google Cloud that enabled a seamless migration. We’ll uncover key lessons, best practices for data lake modernization, and how Yahoo is using BigQuery, Dataproc, Pub/Sub, and other services to drive business value, enhance operational efficiency, and fuel their AI initiatives.

In this session, we’ll explore Google’s latest developments in Google Kubernetes Engine (GKE) that enable unprecedented scale and performance for AI workloads. We’ll dive into how Anthropic leverages these capabilities to manage mega-scale Kubernetes clusters, orchestrate diverse workloads, and achieve breakthrough efficiency optimizations.

Generative AI agents have emerged as the leading architecture for implementing complex application functionality. Tools are the way that agents access the data and systems they need. But building and deploying tools at scale brings new challenges. Learn how MCP Toolbox for Databases, an open source server for gen AI tool management, enables platforms like LangGraph and Vertex AI to easily connect to enterprise databases.

Join us for an interactive session where we’ll build, deploy, and scale inference apps. Imagine creating and launching generative AI apps that deliver personalized recommendations and stunning images, all with the unparalleled efficiency and scalability of serverless computing. You’ll learn how to build gen AI apps effortlessly using Gemini Code Assist; deploy gen AI apps in minutes on Cloud Run, using Vertex AI or on-demand, scale-to-zero serverless GPUs; and optimize the performance and cost of AI workloads by implementing best practices.

Learn how to evaluate and optimize the impact of AI-assisted software development with Gemini Code Assist. This session covers processes for measuring AI-assistance effectiveness, exploring quantitative and qualitative measures available with Gemini Code Assist, and integrating with Cloud Monitoring and Cloud Logging. Discover how to leverage DevOps Research and Assessment (DORA) metrics to track productivity gains. Whether you’re a developer, team lead, architect, or IT manager, you’ll gain insights into measuring the impact of AI assistance.

AI-enabled browser agents are in the news now, but it’s not always clear how they solve real-world problems. In this session, we’ll share our experience building a web browser agent by integrating Gemini into an end-to-end service that follows text instructions to take actions in a web application. We’ll take you through our journey of creating the agent, share the research that inspired us, and show how we’ve used the system to tackle practical problems like validating user flows in the UI and semantically checking web links.

Imagine starting your workday with AI agents at your fingertips, from right within your browser. Join us in this session to learn how Google Agentspace, seamlessly integrated with Chrome and NotebookLM, can change the way you approach work. Think of automating your personal workflows, accessing critical information instantly, and working in unison with AI – all within your familiar browser environment.

Is your platform ready for the scale of rapidly evolving models and agents? In this session, we’ll explore strategies for scaling your cloud native AI platform - empowering teams to leverage an increasing variety of AI models and agent frameworks. We’ll dive into tools and practices for maintaining control and cost efficiency while enabling AI engineering teams to quickly iterate on Google Kubernetes Engine (GKE). We’ll explore how NVIDIA NIM microservices deliver optimized inference with minimal tuning. 

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According to Andreessen Horowitz, 93% of Fortune 500 companies surveyed currently use three or more AI model providers, and now AI agents will proliferate and become standard. With the massive shift in enterprise AI adoption and the pace of change, enterprises need to modernize their network and security to unlock the value that AI generates and keep pace with rapid changes. Learn how to make your network and security AI-ready, plus discover new innovations to reduce infrastructure costs, improve user experience, enable faster developer velocity, and protect your AI infrastructure from new security threats.

This talk demonstrates a fashion app that leverages the power of AlloyDB, Google Cloud’s fully managed PostgreSQL-compatible database, to provide users with intelligent recommendations for matching outfits. User-uploaded data of their clothes triggers a styling insight on how to pair the outfit with matching real-time fashion advice. This is enabled through an intuitive contextual search (vector search) powered by AlloyDB and Google’s ScaNN index to deliver faster vector search results, low-latency querying, and response times. While we’re at it, we’ll showcase the power of the AlloyDB columnar engine on joins required by the application to generate style recommendations. To complete the experience, we’ll engage the Vertex AI Gemini API package from Spring and LangChain4j integrations for generative recommendations and a visual representation of the personalized style. This entire application is built on a Java Spring Boot framework and deployed serverlessly on Cloud Run, ensuring scalability and cost efficiency. This talk explores how these technologies work together to create a dynamic and engaging fashion experience.