The Linux Foundation Member Summit 2025

The SBOM (Software Bill of Materials) for a single automotive vehicle is in high demand. Modern vehicles are advanced information systems that constantly evolve, with frequently changing software configurations. This trend is even more pronounced in Software Defined Vehicles (SDVs). Open source supports this evolution. Understanding the software components that make up a vehicle is crucial for asset and risk management, making it a valuable endeavor in the software supply chain. The introduction of process management standards like ISO 5230 and ISO 18974, and the adoption of standard data formats through SPDX Lite (ISO 5962 (SPDX 2.2.1) and the annex of SPDX 2.3), are expected to yield significant results. Meanwhile, there is growing interest in more effective SBOM content and how to share and handle this information. In this session, we will share insights and challenges gained through the development of IVI.

Growing new talent and attracting new developers is challenging for open source communities. Yet, it is vital to reach out to train the next generation of developers to keep the open source communities healthy and sustainable.

Equitable access to learning resources is a barrier for a significant number of new developers. It isn't easy for new developers to get a start in open source, connect with open source communities and contribute to them. It is equally challenging for employers to find new developers to add to their technical projects.

Shuah Khan will talk about Linux Foundation's six year journey to provide learning resources for new open source developers, opportunities to experts in open source communities to train and mentor the next generation, and make newly trained talent available to prospective employers.

Undertaking effective data governance in AI training has become a central issue among Open Source AI advocates due to the complex nature and diversification of shared data resources. To have effective governance requires navigating a matrix of rules and ethical principles to protect copyright, privacy and other data-related rights. Effective data governance must also consider the impact on fundamental rights, ensuring that equitable and inclusive standards are maintained within AI ecosystems and the oversight of such systems.

In this talk I will discuss the role of data governance and data sharing as they relate to Open Source AI development. Specific approaches and strategies will be shared that can be undertaken both by Open Source AI developers and by other stakeholders to increase the amount of data that is properly governed and available for use in Open Source AI development.

The U.S. is facing a critical talent shortage, with companies struggling to hire the best international professionals due to restrictive visa policies and the uncertainty of the H-1B lottery. Open Avenues Foundation has developed a groundbreaking solution that not only provides companies with an alternative pathway to hire top foreign talent but also invests in the future of the U.S. workforce.

Through its national Fellowship program model, Open Avenues partners with tech and scientific companies by obtaining a cap-exempt H-1B visa for the company’s key foreign national personnel who has no other option to work in the United States, without the requirement to win the H-1B lottery. Open Avenues then employes the highly skilled foreign professional for five-hours per week to train U.S. college students in the foreign national’s STEM profession. Once the foreign national has an approved part-time cap-exempt H-1B with Open Avenues, the law permits the tech or science company to immediately file its own concurrent cap-exempt H-1B for the same person, also without needing to win the H-1B lottery. This program provides international talent in the Fellowship to work for high-growth companies and contribute to the U.S. economy while concurrently preparing the next generation of American workers with the skills they need to compete globally.

Join Danielle Goldman and Jeff Goldman, Co-Founders of Open Avenues Foundation, as they share how this innovative approach is transforming both immigration and workforce development. Learn how business leaders can use this model to attract and retain global talent, strengthen their hiring pipeline, and stay competitive in today’s evolving economy.

If 2023 is the year of LLMs, then 2024 will be the year for LLM Applications. As LLMs continue to integrate into various applications ranging from chatbots and search engines to creative writing aids, the need to monitor and comprehend their behaviors intensifies.

Observability plays a crucial role in this context. It involves the systematic collection and analysis of data to enhance LLM performance, identify and correct biases, troubleshoot issues, and ensure AI systems are both reliable and trustworthy.

In this discussion, we will explore the concept of LLM observability in depth, focusing on how OpenTelemetry can fit into the world of LLM observability . Additionally, we will talk about challenges around modeling of prompts, completions, events, semantic conventions, and basically our path with the llm-sem-conv working group.

Open source is everywhere. Anyone can use it and anyone can contribute codes to the community regardless of the countries and regions. It is inherently borderless.In the meantime, it is also true that most of the critical open source projects are English speaking communities. This actually creates a gap between English speaking regions and non-English speaking regions in terms of the knowledge about the technologies as well as opportunity to get involved in the community development. There has to be a “Bridge” to fill the gap.

The Linux Foundation Japan office launched a program to solve this issue by launching the Japan Evangelist Program, which has been a big success so far. The evangelists can also become a community by itself, they become a force to connect multiple communities to co-work to create larger values as well as sharing best practice to run meetup etc, which has been a nice side effect of the program.

In this session, through the discussion with the panelists (they are all Japan Evangelists) we would like to elaborate how the program is actually working.

The rapid evolution of large-scale AI models has been fueled by open-source contributions across four critical dimensions: models, data, evaluation, and system software. To access the real impact of these contributions, we conducted the first large-scale, cross-platform study over six months, investigating nearly 100,000 data points from platforms like Hugging Face, GitHub, and ModelScope. This study, carried out by key contributors from BAAI, CSDN, Linux AI & Data, and other leading organizations—provided deep insights through monthly evaluations, revealing trends, challenges, and opportunities in the open-source large model ecosystem.

In this presentation, we will decode the current state of open-source large model technology, highlight key findings from this groundbreaking collaborative analysis, and discuss its implications for future innovation. From tracking global adoption patterns to identifying critical gaps in open-source collaboration, attendees will gain a deeper understanding of how open-source efforts drive AI development today and the strategies needed to shape the next wave of breakthroughs.