| 12:30 PM | Check-in | |
| 1:00 PM | Welcoming notes | |
| 1:10 PM | From DevOps to MLOps | This session explores the evolution from DevOps to MLOps, focusing on the integration of Machine Learning (ML) workflows into traditional DevOps practices. Attendees will gain insights into the challenges, tools, and best practices involved in managing ML models and pipelines effectively in production environments, ensuring seamless collaboration between data scientists, developers, and operations teams. |
| 1:40 PM | AIOps: yet another buzzword! | With the emergence of generative AI and the dazzling success it has achieved in just a few months, companies are asking a lot of questions about the relevance of AI and its fields of application overall domains. After DevOps, FinOps or even DevSecOps, it was time to attach the term AI to the profession of ops to give birth to AIOps practices where we will use AI to help ops on a daily basis and enable them to win considerable time with prevention, optimization or even smart assistance in their everyday work. |
| 3:00 PM | Workshop: Fine-tuning Gemma LLM models | Learn how to fine-tune Gemma models |
| 3:00 PM | Firebase meets Google Cloud | Do you use Firebase, but sometimes face limitations and wish to extend beyond? Or, have you not heard of it before, and wish to focus on building your apps instead of managing cloud resources? This talk is a quick journey into both worlds, where we will demonstrate what best fits your growing app needs, from managed to customized services on the cloud. |
| 3:30 PM | Keeping Up with AI: Gemma’s Here So You Don’t Get Left Behind | Feeling like AI is moving faster than your morning coffee? Don’t worry, you’re not alone! In this session, we’ll dive into Gemma – Google’s latest AI wizardry – designed to help you keep up with the ever-changing world of machine learning. Whether you’re already deep into AI or just trying to stay in the game, Gemma’s got your back with tools and techniques that simplify model training without breaking a sweat. So, join us to learn how to stay ahead of the curve, harness the power of GenAI, and make sure you're always one step ahead of the bots! |
| 4:20 PM | Crafting AI-Driven Games with Gemini and Flutter | Discover how to harness Flutter's full potential to create immersive, AI-driven 2D games. In this session, we'll build a dynamic Flutter app using the powerful Flame Engine, seamlessly integrated with Google's Gemini AI. We'll also explore the synergy of using Dart on the front and backend, leveraging Dart Frog as a robust backend solution.
We'll guide you through crafting a game that not only looks and feels engaging but is also powered by cutting-edge AI. Learn how to seamlessly integrate Gemini to create smarter, more responsive game environments while maintaining a consistent development experience with Dart across the entire stack.
Whether you're a seasoned developer or just starting in game development, this session will give you the tools and knowledge to elevate your projects. Join us and take your first steps toward building the next generation of AI-powered games with Flutter, Flame, and Gemini! |
| 4:50 PM | Build Mobile apps at a scale | How do you build a Flutter app that can handle millions of users? In this session, I’ll share the real-world lessons we learned building Drahim from scratch and scaling it up to support a massive user base. We’ll cover what worked, what didn’t, and the strategies that helped us create a smooth, reliable experience as we grew. From optimizing performance to managing state and handling data efficiently, this talk is all about practical tips for building Flutter apps that are ready to scale. |
| 5:10 PM | AI and Privacy Regulation Landscape in the Kingdom of Saudi Arabia | Saudi Arabia’s Vision 2030 emphasizes AI as a key driver of economic growth, especially in sectors like healthcare and smart cities. With this comes the critical need for privacy protections as AI relies heavily on personal data. The presentation explores the current privacy regulation landscape, particularly under the Personal Data Protection Law (PDPL), and its impact on AI. Key considerations for businesses include data governance, compliance requirements, and ethical AI practices. This regulatory framework aims to ensure innovation aligns with user privacy and trust. |
| 5:30 PM | Pizza time 🍕 | |
