Real-time demonstration: Feed the knowledge graph into GenAI. Watch AI analyze process bottlenecks with full enterprise context. Interactive session: Audience can join the optimization process live.

Using GenAI/LLMs to create and backtest trading strategies.

In the news, GenAI is usually associated with large language models (LLMs) or with image generation tools, essentially, machines that can learn from text or images and generate text or images. But in reality, these models can learn from many different types of data. In particular, they can learn from time series of asset returns, which is perhaps the most relevant for asset managers. In this talk, and in our accompanying book (Generative AI for Trading and Asset Management), we highlight both the practical applications and the fundamental principles of GenAI, with a special focus on how these technologies apply to trading and asset management.

explores how GenAI is transforming how we access and interact with online content.

Models need up-to-date facts (data) to solve tasks. But data (retrieval) needs models, too: for semantic search and for ranking top candidates. At this meetup, we will go through the data/model interplay: you will learn how to transform problems into the numeric domain using tensors, and with this, work with text, image, and videos. We’ll do live demos from e-commerce and media. Whether it’s personalizing the shopping experience in real time or finding the next song to autoplay, this session will help you think beyond LLMs—and design retrieval-first GenAI systems that deliver real-world impact.

Abstract: Models need up-to-date facts (data) to solve tasks. But data (retrieval) needs models, too: for semantic search and for ranking top candidates. At this meetup, we will go through the data/model interplay: you will learn how to transform problems into the numeric domain using tensors, and with this, work with text, image, and videos.\nWe’ll do live demos from e-commerce and media. Whether it’s personalizing the shopping experience in real time or finding the next song to autoplay, this session will help you think beyond LLMs—and design retrieval-first GenAI systems that deliver real-world impact.

This isn’t a “what if” conversation — it’s a behind-the-scenes look at real GenAI deployments from women leaders across different domains. Each speaker will share the tools, workflows, and measurable results from their projects — plus the lessons learned along the way.

Do you often get asked about the newest GenAI use cases? Or maybe you've run into a puzzling Langchain error? If so, this session is for you. You'll see how at Mollie, we tackled these challenges by building our own framework GaaS (GenAI as a Service). We'll show you how developing an in-house GenAI platform speeds up development and streamlines AI adoption across teams. By building together concrete examples, you'll learn how a centralized REST API can make AI tools easy to use for everyone—giving each business unit a secure and efficient way to build their own AI-powered solutions. Whether you're just starting out or looking for real-world inspiration, you'll walk away with practical insights to boost your next AI project.

Practical talk on GenAI, including a step-by-step walkthrough of building an app with OpenAI APIs and Next.js; discusses capabilities and limitations of GenAI for web development.

Strategies for transforming teams and processes to be AI-ready and scale GenAI-enabled DevOps.

Exploration of practical GenAI use cases for developers and operations teams in DevOps workflows.

Overview of the technical foundations enabling smarter automation in modern DevOps with GenAI.

Successful gen AI projects strike the balance between impact, accuracy and cost - in this talk, we cover how to create agentic data applications effectively, choosing when and how to integrate them in data streams and keep response quality issues and costs in check.

Kannupriya Kalra and Rory Graves discuss GenAI in Scala with LLM4S, walking through live demos—from basic LLM calls and RAG search to image processing and AI-driven code writing. The talk covers building powerful GenAI-powered Scala applications and tools, with practical guidance on architectures, integration, and scalability.

Overview of identity/entity resolution in fraud prevention, marketing, and GenAI applications, with real-world implications.

Adrian Boguszewski is an AI Software Evangelist at Intel. He graduated from the Gdansk University of Technology in the field of Computer Science 8 years ago. After that, he started his career in computer vision and deep learning. As a team leader of data scientists and Android developers for the previous two years, Adrian was responsible for an application to take a professional photo (for an ID card or passport) without leaving home. He is a co-author of the LandCover.ai dataset, creator of the Debug Image Viewer Plugin, and a Deep Learning lecturer occasionally. His current role is to educate people about OpenVINO Toolkit. In his free time, he’s a traveler.

Overview of real-world, budget-friendly AI use cases at DFKP, including GenAI-powered document handling, automated customer profiling, smart lead routing, and offer generation.

As generative AI (GenAI) becomes increasingly embedded in the game development pipeline, from character creation to procedural world-building, it brings with it both exciting possibilities and ethical challenges. This talk explores how GenAI tools are shaping the future of games, and asks: Who might be left out of what we are designing? Focusing on issues of gender, queer, neurodiversity and intersectional inclusion, this talk will examine how bias can enter at every stage of the development process and how these biases can impact both players and creators.

Unlock the power of generative AI and vector search to transform vague queries into precise results. Discover practical Python examples and see how advanced search revolutionizes user interaction and business outcomes.