Open Source Summit Europe 2024

Discover how an open-source, end-to-end DataOps stack is being developed to manage connectivity and infrastructure data for over 2 million schools. This session will cover key components including data ingestion mechanisms, pipelines, data quality, metadata and master data management, data cataloging, data APIs, analytics & visualisation, data lake storage, and ML notebook management—all integrated with error and change notification systems.

Open source brings the promise of an AI market that is decentralised, competitive, user-centric, and where Europe leads. With this explosion, open source communities and policymakers are asking questions about open source AI’s innovation benefits, safety risks, impact on sovereignty, and competitive economics against closed-source models. In this fireside chat, OSI board member and Microsoft open source lawyer Justin Colannino will interview OFE's Sachiko Muto, OSI's Stefano Maffulli, and LF’s Cailean Osborne about why a clear and consistent definition of open source AI matters for open source communities in the face of growing EU policy tending towards greater open source regulation. We will focus on how truly “open source” in AI manifests in practice and how can it be can bolster European competitiveness while keeping true to all of our open source values.

The decentralized fediverse is poised to revolutionize how we interact online, but it still lacks a crucial component: standardized, interoperable AI agents. Current AI agent frameworks are numerous, but fragmented, leading to inefficiencies and duplication of effort. This talk proposes a future vision where decentralized fediverse is empowered by standardized, autonomous AI agents with human-in-the-loop, enhancing our daily lives both online and offline. We'll discuss the need for a standard architecture for AI agent frameworks, incorporating AI safety rules and sustainable development principles, to ensure the new "AIverse" is built responsibly and sustainably. Join us in exploring how this vision can become a reality.

RISC-V, an open-standards Instruction Set Architecture (ISA), provides the freedom to add instructions for domain-specific acceleration. This session highlights the significance of ongoing standardization efforts at RISC-V aimed at enhancing AI/ML capabilities through specific architectural enhancements: optimized instructions for matrix operations, efforts to merge GPGPU-style processing into a coherent, multi-paradigm compute resource, and support for emerging paradigms like spiking neural networks. This positions RISC-V to become a "lingua franca" for portable AI/ML libraries and kernels that can transparently be moved between compatible hardware from multiple vendors.

Learn how combining traditional NLP techniques with LLMs can solve 'hallucination' issues and create robust applications. This session offers practical insights into leveraging foundational NLP principles alongside advanced LLM technology. It's based on a business problem where the need is to craft technical content that directly tackles the key challenges customers encounter. Rather than wading through hundreds of public forum posts or customer complaints manually, why not harness the combined power of traditional, explainable Natural Language Processing (NLP) techniques integrated with the advanced language generation capabilities of Large Language Models (LLMs). This session will provide architecture and lessons learned in the journey to uncover insights from our users' feedback. Centered around a topic modeling use case, this session offers actionable insights that go beyond mere buzzwords. At the end the audience will learn how to leverage text analytics and the strengths of Open Source LLMs to tailor content that resonates with their audience's needs and pain points. Bonus points: This use-case architecture is completely automated using CI/CD principles.