This talk dives deep into the top AI skills that are shaping the future of the field, drawing insights from cutting-edge research, open-source contributions, industry trends, and job market analysis. From foundational proficiencies in programming, machine learning, and data wrangling to emerging specialties like AI Agents, prompt engineering, and generative AI expertise, we’ll explore what it takes to excel in 2025. Designed for AI practitioners, developers, tech leaders, students, and business professionals, this session offers actionable insights tailored to every audience. This session is your roadmap to the skills and trends that will define the next wave of AI innovation, helping you stay ahead in an ever-evolving landscape.

Vanilla Retrieval-Augmented Generation (RAG) is becoming more and more adopted - but What is next? Join us for an introduction to Generative Feedback Loops (GFL). GFLs can level-up your RAG architecture by generating more insights on top of your data. This empowers you to implement smarter chatbots, agents, and other AI-driven solutions. Based on hands-on examples, we will explore the following questions: a) What are GFLs are? b) How do GFLs work? c) What challenges and use-cases can we tackle with GFLs; and d) How can I define my AI workflows to implement GFLs. Learn about the next level of AI applications and join us for a Live Demo.

Large language models unlock exciting new opportunities - but there's still lots of hard work to do for engineers, designers and product managers to turn foundation models into products users love! In this session, you'll learn about GitHub's journey building Copilot code review, currently in public preview, and the lessons learned along the way.

Panel discussion exploring essential AI skills, talent retention, innovative technologies, education partnerships, mentorship, and continuous learning. What You Will Learn: Essential Skills for AI: Identify the most sought-after skills for AI developers today and discover pathways for students and junior developers to gain them; Talent Retention Strategies: Explore effective methods for attracting and retaining top AI talent, ensuring your teams remain competitive; Innovative Technologies: Find out which emerging technologies could shape the next wave of AI innovation, such as quantum computing and generative AI; Strengthening Education Partnerships: Learn how collaboration between educational institutions and industries can enhance AI skill development; The Power of Mentorship: Discuss how mentorship can significantly impact the growth of AI talent and how to implement successful programs; Cultivating Continuous Learning: Discover strategies for fostering a culture of learning within organisations to keep AI teams innovative and competitive.

What you'll learn: Introduction to Generative AI; Importance of Generative AI; Technical foundations and terminology; Evaluating risks and mitigations; Prepping Organization for GenAI initiatives.

Next generation developer tools that incorporate generative AI are everywhere, but how good are they, and. more importantly, how useful. In this talk I am going to share what I have learned from using these tools over the last 12 months. I will cover the kinds of day-to-day scenarios and use cases I am finding them useful for, how they are helping me address some of my developer problems, and tips I have learned to more effectively use these tools. This session contains live coding/demos that will help you see this in action.

Learn the ABC's of incorporating generative AI in your commercial applications with the Development Expert at SAP, Marika Marszalkowski. She will guide you on manifesting chat functionality into your native TypeScript or JavaScript application and ensuring it's suitable for your business software environment.

Explore the nuances of utilizing prompt templates in generative AI applications with Thomas Schneider, a proficient AI Developer at SAP. He will share his experiences, focus on the challenges, opportunities, and most importantly, manage the prompt templates throughout the user journey.

Next generation developer tools that incorporate generative AI are everywhere, but how good are they, and. more importantly, how useful. In this talk I am going to share what I have learned from using these tools over the last 12 months. I will cover the kinds of day-to-day scenarios and use cases I am finding them useful for, how they are helping me address some of my developer problems, and tips I have learned to more effectively use these tools. This session contains live coding/demos that will help you see this in action.

Fundamentals of Generative AI and LLMs; best practices for building AI solutions on AWS; overview of AWS services like SageMaker; real-world applications and case studies.

Discover the basics of generative AI, including core models, functionalities. Learn how to utilize these models to build your own generative AI applications.

In this session, we will focus on fine-tuning, continuous pretraining, and retrieval-augmented generation (RAG) to customize foundation models using Amazon Bedrock. Attendees will explore and compare strategies such as prompt engineering, which reformulates tasks into natural language prompts, and fine-tuning, which involves updating the model's parameters based on new tasks and use cases. The session will also highlight the trade-offs between usability and resource requirements for each approach. Participants will gain insights into leveraging the full potential of large models and learn about future advancements aimed at enhancing their adaptability.

Introduction to AI and ML on Google Cloud; Exploring Data-to-AI Technologies and Tools; Harnessing Generative AI Capabilities; Choosing the Right Option for AI Development; Building ML Models with Vertex AI

One of the key players behind the staggering speed of advancement in machine learning and AI are foundation models. But what is a foundation model, really? In this talk, I’ll explain what exactly defines a foundation model, what they’re capable of doing, and review some well-known examples of foundation models in the real world.

In this session, I will share how I have approached learning the foundations of Machine Learning to transition into a role as an ML engineer, despite my non-traditional background. How I use chatgpt and other generative AI tools to assist both at work and on my side projects. The pros and cons I see of using these tools and why I think it's important we take notice of these technologies.

An insight into how the power of GenAI can improve interaction with your customers and agent productivity.

Overview of Generative AI concepts and their business and technical implications.

Foundational concepts and terminology related to Generative AI and GenAI technologies.

GenAI Deep Dive talk by Sana Shah, Founder & UG Lead (AWS WUG).