Munich Datageeks June Edition
Education

Munich Datageeks June Edition

À propos de l'événement

As always, there will be plenty of time for networking, discussions, and snacks & drinks courtesy of our host.
📍 Event Details
📅 Date: Tuesday, June 23rd, 2026

🎤 From Frankensteining DeepSeek to Mixture-of-Experts: The R1T Chimera Models
by Fabian Klemm, TNG Technology Consulting GmbH

At TNG an internal AI research group has been experimenting with Mixture-of-Expert Large Language Models and adaptions of the DeepSeek model family. First they manipulated the way experts work within a model under the name Mixture of Tunable Experts. They then continued with the Assembly-of-Experts merging process resulting in the Chimera models which gained severe attention with daily usage of more than 10 billion tokens via OpenRouter.

About Fabian Klemm:
Dr. Fabian Klemm completed his doctorate at the Technical University of Munich (TUM) in discrete mathematics and applied geometry. There, he worked on clustering problems under constraints in general geometric spaces, before switching to IT in 2020 and joining TNG as a Software Consultant. In addition to extensive DevOps experience, Fabian has developed a strong interest in AI – especially LLMs – particularly in mechanistic interpretability and Large Language Model architectures. Fabian is currently part of the TNG AI research team that published the DeepSeek Chimera models. He also contributes to the TNG Skainet team, which operates TNG’s internal AI server rack.

🎤 From Models to Systems: How PAYBACK built an AI Platform for Production ML
by Artemii Frolov, PAYBACK & Mohammed Hatem Moustafa, PAYBACK

Building one ML model is hard. Enabling numerous cross-functional teams to ship and operate models reliably is a entirely different game.
This talk shares how PAYBACK built an internal AI Platform on top of Google Cloud to let delivery teams build, deploy, and run ML models in production - without reinventing the pipeline every time. From an engineering angle, we cover how the platform standardizes modular,

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