AI Innovator Munich with Weights & Biases × JetBrains

​Join us for an evening dedicated to building practical, production-grade AI applications. Weights & Biases and JetBrains are bringing together machine learning engineers, software developers, MLOps practitioners, and AI builders to explore how modern developer tooling, experiment tracking, evaluation workflows, and scalable infrastructure help turn prototypes into reliable, production systems. Expect technical depth, live demos, and real-world lessons on topics like experiment tracking at scale, debugging and evaluating LLM-based applications, and bridging the gap from notebooks to deployed AI features.

​Featured Session from Weights & Biases:

​Serverless Reinforcement Learning for Specialized LLMs
Discover how Serverless Reinforcement Learning (RL) can unlock advanced reasoning for specialized models — dramatically reducing infrastructure overhead and training latency while replacing slow general-purpose models with fast, intent-aligned AI agents.

Featured Session from JetBrains:

​AI Agents in the JVM World
The first frameworks for building AI agents primarily targeted Python and JavaScript, leaving the JVM ecosystem behind. But in just a year, the landscape changed dramatically. New JVM-based agentic frameworks such as LangChain4j, Koog, Spring AI, and Embabel have entered the scene.

​In this talk, Maria Tigina shares the JetBrains journey from Python-based agents to Kotlin, which ultimately led to the release of Koog. She’ll explore the advantages and trade-offs of building AI agents on the JVM, and look at real examples where strong domain modeling and type safety play a crucial role in making AI agents more stable, interpretable, and production-ready.

​Who should attend:
AI/ML engineers, platform teams, software developers, and anyone pushing AI innovation into real-world products.