Armand Angeli, Vice President International & Digital Transformation Groups, DFCG, Room Universe
Dr. Rahim Malekshahi, Specialist Strategic Foresight, BSH Home Appliances Group and Eric Joachim Liese, Strategic Advisor and Lead Architect for AI & Data, BSH Home Appliances Group, Room Universe
Wouter Kokx, Associate Partner, McKinsey & Company and Ferry Grijpink, Partner, McKinsey & Company, Room Universe
Dr. Djalel Benbouzid, Trustworthy AI expert, AIAAIC, Room Universe
• Multi-agent LLMs and corporate processes optimisation
• AI Act compliance
• SLM and data confidentiality
Nico Bitzer, Co-Founder & CEO, Bots & People, Stiv Sterjo, Smart Analytics & AI Cluster Lead, Google and Dimitri Metzger, IT Business Partner for Healthcare R&D, Merck, Room Universe
Join a distinguished panel of CIOs and executives as they explore not only the technical complexities of implementing Gen AI but also the essential human aspects that drive success in large organizations. This session will offer a balanced perspective, highlighting both cuttingedge strategies and the people-centric approaches needed to embed AI at scale. Designed for both Gen AI experts and business leaders, the discussion will provide actionable insights into navigating large-scale AI deployment while empowering your workforce.
• Upskilling and Workforce Training: How can organizations effectively reskill and train employees to harness Gen AI? Explore best practices for continuous learning, digital fluency, and creating a culture of innovation.
• Communication and Change Management: Understand the role of transparent communication in minimizing resistance to AI adoption. Learn how to guide teams through the cultural and organizational shifts brought by Gen AI technologies.
• Architectural Frameworks: Designing robust, scalable AI systems while fostering collaboration between human experts and AI tools.
• Advanced Integration Techniques: How to integrate Gen AI seamlessly within existing IT infrastructures while ensuring cross-functional collaboration.
• Optimization and Scalability: Techniques to optimize AI models not only for performance but also for human-centered design, ensuring that the technology enhances productivity without overwhelming teams.
• Data Management, Security, and Ethical Considerations: Establishing secure, ethical data management practices, while building trust among employees and ensuring regulatory compliance.
• Human-AI Collaboration: Developing systems where AI augments human creativity and decision-making, rather than replacing human workers, ensuring a smoother transition to AI-powered workflows.
By focusing on both the human and technical elements of AI deployment, this panel will provide a comprehensive roadmap for organizations aiming to leverage Gen AI while empowering their people
Pooja Bhatia, Data & AI Cloud Solution Architect, Microsoft, Room Universe
• Gen AI-Driven Innovation: Potential of Gen AI frameworks and tools and their capacity to
revolutionize industry landscapes
• Agentic RAG: Its distinction from the conventional RAG, integration into existing systems,
and strategies for deployment
• Multimodal LLMs & SLM: The latest advancements in MLLM. The significant influence of
smaller models like SLM and Microsoft’s role in reshaping the AI model domain
• GraphRAG: A novel approach that enhances the traditional RAG by incorporating graph-
based data structures, how it augments the model’s decision-making process and
various framework
Donatien Chedom Fotso, Head of Applied AI - CB Data Science CoE, Deutsche Bank, Room Universe
Michel de Ru, Head of Solution Engineer, EMEA, DataStax and Jurriaan Krielaart - Account Executive, EMEA, DataStax, Room Universe
Unlock the true potential of AI by bringing it directly to your data. In this webinar, discover how integrating contextual intelligence enhances relevance and delivers deeper insights. Learn why your unique IP is key to sustainable success in generative AI and how aligning
AI with your proprietary data can create a lasting competitive edge. Don’t miss out on strategies to future-proof your AI initiatives—register now!
• AI merely levels the playing field for enterprises
• How they gain sustained value from AI for organizations
• Lots of prototyping going on, what does it take to actually productize AI
• What are some of the new techniques that actually make a difference in relevancy,
preventing hallucinations
Aleksander Djurka, Head of Data Engineering and Infrastructure, Stellantis, Room Neptune
In the era of Generative AI, the success of AI initiatives hinges on more than just algorithms—it depends on robust, scalable data platforms. This talk explores the pivotal role of data platforms in accelerating AI use case development. Drawing from experiences across multiple industries, we’ll delve into strategies to enable rapid deployment, ensure compliance, and optimize the ingestion of data into AI systems like Retrieval-Augmented Generation (RAG). The presentation will highlight the importance of leveraging unique data versus investing in state-of-the-art algorithms, and how data mesh principles combined with the separation of storage and compute can streamline AI integration. The goal is to leave you all with actionable insights into designing data platforms tailored for GenAI success.
Eric Joachim Liese, Strategic Advisor and Lead Architect for AI & Data, BSH Home Appliances Group and Saif Addin Ellafi, Product Lead, MLOpsData Engineer, Solutions Architect, BSH Home Appliances Group, Room Neptune
• What is and why do RAG
• Building and Deploying RAG IaaS
• Reusable and customizable components
• Getting and maintaining data for the LLM
• Quick start use case onboarding formula
• Common boilerplate frontend (Streamlit)
• Reusable observability and monitoring
Iliana Portugues, VP Innovation Centre Berlin, Siemens Energy, Room Neptune
• Exploring LLMs for product portfolio management
• Leveraging LLMs in operational situations to drive
product and service improvements
• Improving manufacturing through the use of AI
tools
Elie Bakouch, AI Research Engineer, Hugging Face, Room Neptune
• Smol LMs are ideal for today’s applications, delivering efficiency without the complexity of massive models; for example, handling routine tasks like summarizing emails or generating quick responses doesn’t require the power of GPT-4.
• Smaller models offer faster processing times and lower costs, making them ideal for edge devices and real-time applications. They also reduce energy consumption and enable on-device operation, enhancing privacy.
• There are ways to enhance these models for better performance, and they’re far more accessible for individual developers and small businesses compared to larger models.
Dinos Metaxas, Chief Digital & Marketing Officer, L’Oréal and Tomasz Chyrchel, Senior Innovation Manager - AI Lead, L’Oréal, Room Jupiter
Dimitri Metzger, IT Business Partner for Healthcare R&D, Merck, Room Jupiter
Dieter Konrad, Expert Capital Market Data Science, Union Investment, Room Jupiter