IBM at Open Source Summit Europe 2025

Description:

IBM is dedicated to promoting Responsible AI by equipping developers with cutting-edge tools that improve fairness, transparency, and accountability of AI systems. In line with this effort, this session is designed to introduce Granite Guardian, an open-source suite of AI models that allow developers to monitor AI systems, mitigate bias, and comply with regulations. Granite Guardian is not just an open-source suite of AI models; it is a comprehensive AI governance framework, a strategic enabler for creating responsible, transparent, and compliant AI at scale. Attendees will leave this session with knowledge of AI governance and a set of tools that allow them to create, launch, and manage AI responsibly. Whether they are developers who already embed ethical AI behaviour into their designs, or industry leaders aligning with ethical and regulatory guidance, this session will empower them to create scalable, not just sustainable, AI.

Speaker: Shalini Harkar

Description:

As the modern applications running on Kubernetes become more dynamic, a reliable stateful storage becomes essential. These applications don’t just need storage; they need it to be fast, intelligent, and cost-effective.  With so many open source tools available—like Rook-Ceph, NooBaa, and Longhorn—how do you pick the right one? And once you do, how do you make sure it’s reliable and doesn’t break the budget?

In this session, we’ll discuss how one can use open storage in Kubernetes—what works well, what causes problems, and how to avoid common mistakes. We’ll cover storage for different use cases (like block, file, and object), and talk about features like dynamic provisioning, snapshots, and scaling.

Whether you're a developer, architect, or admin, this session will help you understand how to choose, deploy, and manage open source storage in Kubernetes.

Speaker: Shriya Mulay

Description:

As AI systems proliferate, ensuring transparency, trust, and traceability across the model supply chain has become a critical challenge. The Model Openness Framework (MOF), developed by LF AI & Data and Generative AI Commons, offers a standardized classification system to evaluate the completeness and openness of AI models across 17 key components—from architecture to evaluation code and documentation. This talk will explore how the MOF addresses model "openwashing" and supply chain risk by establishing clear standards for licensing and disclosure. We will demonstrate how enterprises can operationalize MOF compliance using open source tools like OCI-based model packaging, model signing, and automated documentation pipelines. Attendees will gain practical insights into aligning with emerging governance requirements and building trustworthy, reproducible AI systems through open collaboration.

Speakers: Vincent Caldeira, Red Hat & Arnaud Le Hors, IBM

Description:

Client server computing relies on encryption algorithms to ensure that data sent across networks cannot be read, or faked, by untrusted parties. This is the rock on which financial computing works in a business to customer environment, as well as how data at rest is protected from malicious prying eyes reading our personal data.

This talk will cover the basics of how Diffe-Hellman encryption works, how symmetric and asymetric keys operate, as well as how all of this will soon become unsafe because of quantum computing. As well as showing the audience the basics (no maths degree required) this talk will show how quantum safe encryption is able to address this, and how folks can get wise and get started.

Speaker: Joe Winchester