Munich Datageeks August Edition

We are thrilled to announce our next Meetup on August 21st at KPMG.
Format:

• 2 talks (each ca. 40 min incl. discussion)
• Time for networking + food + drinks before, in between and after the presentations
• Talks are held in English
• We will be taking photos and/or film footage at the event. These will be used to share news about our meetups and to publicize upcoming events.

The lineup:

First talk:
Linus Teklenburg - Leveraging Business Operations with AgenticAI: From Transformer Architecture to Secure Enterprise Applications

Abstract:
In recent years, transformer architectures have redefined what machines can understand, generate, and automate. From their roots in natural language processing to their influence on vision, code, and beyond, these models laid the foundation for a new paradigm: Agentic AI. In this talk, we trace the evolution from transformer-based models to autonomous, goal-driven AI agents capable of reasoning, interacting, and operating in enterprise environments. We explore how businesses can harness these agents to optimize operations, unlock latent value, and enable decision-making at machine speed — all while maintaining strict standards of compliance, governance, and security. Attendees will gain insights into the practical deployment of GenAI and agent-based systems, real-world use cases, and the architectural considerations required to move from innovation to implementation. This is not just a look at where AI stands today — it’s a vision of where it’s heading, and how enterprises can lead rather than follow.

Bio:
Linus Teklenburg is an AI developer and consultant at KPMG. He studied artificial intelligence at the Technical University of Ingolstadt and specialises in applied AI solutions, initially in the field of computer vision, and later in chatbots and agentic AI. With his technical expertise and consulting experience, he combines innovative technologies with practical applications to develop data-driven solutions.

Second Talk:
Prof. Dr. Martin Spindler - Demand Estimation with (Causal) AI

Abstract:
In the talk we will discuss how modern methods like Causal AI combined with Foundations Models can be used to improve the estimation of demand and to optimize pricing. We will present both the underlying theory and a use case. We use data from Amazon.com to highlight how price elasticity can be estimated utilizing text and images and how heterogenous subgroups can be detected for more granular pricing.

Bio:
Martin Spindler is Professor of Data Science, Statistics & Econometrics at the University of Hamburg and Director at Economic AI. In his research he works on the theory and practical applications of Machine Learning and AI, in particular Causal Machine Learning.
Together with leading researchers he has founded Economic AI to support companies to develop state-of-the-art, tailor-made solutions. The focus is on causal problems like Dynamic Pricing, Targeted Marketing, Marketing Mix Modelling, Production Optimization and advanced A/B Testing. Economic AI provides the software package "DoubleML" which is one of the leading packages for Causal AI and provides trainings on various levels. The clients are leading tech and platform companies (e.g. google, booking.com) and pharma and industrial companies (e.g. Novartis, VW).