ΑΙhub 04月10日 17:07
#AAAI2025 workshops round-up 2: Open-source AI for mainstream use, and federated learning for unbounded and intelligent decentralization
index_new5.html
../../../zaker_core/zaker_tpl_static/wap/tpl_guoji1.html

 

本文总结了AAAI 2025年会上两个重要研讨会的核心内容。第一个研讨会关注“开放AI在主流应用中的实践”,探讨了开放AI模型的定义、政策、工具以及构建开放生态系统中的挑战。第二个研讨会聚焦于“FLUID:无界智能去中心化联邦学习”,深入研究联邦学习在优化、隐私、可扩展性及实际部署中的新兴挑战与机遇,并探讨了其在智慧城市和医学诊断等领域的应用。

💡 开放AI研讨会探讨了开放AI在主流应用中的实践。会议探讨了开放AI模型的定义、监管框架、工具及构建开放生态系统的挑战。其中,Kate Soule (IBM Research)介绍了“Granite: 开放源代码的企业模型”,并分享了其开发细节及在企业应用中的适用性。

📢 开放AI研讨会还深入讨论了“开放源代码与政策”相关议题,包括围绕AI模型“开放性”的定义及监管框架。此外,会议还展示了AI在工业安全、自然语言交互协议等方面的应用。

🛠️ 开放AI研讨会展示了多种“开放源代码工具”,包括文档转换、简化企业AI检索增强生成(RAG)流程、生成式融合解码的后期融合实现以及促进与关系数据库自然语言交互的代理。

🌐 FLUID研讨会聚焦联邦学习与智能去中心化。Holger Roth (NVIDIA)在主题演讲中探讨了理论模型与实际应用之间的差距,强调了大规模部署隐私保护系统所面临的实际复杂性。

📚 Yang Liu (清华大学)介绍了跨异构模型的协同训练,强调设计灵活的学习框架以适应不同的客户端能力和数据分布的重要性。该研讨会还涵盖了高效通信、分割学习架构以及在智慧城市和医学诊断等领域的应用。

Images from the workshop: FLUID: Federated Learning for Unbounded and Intelligent Decentralization. Workshop chairs Marzia Canzaniello and Daniela Annunziata.

In this series of articles, we’re publishing summaries with some of the key takeaways from a few of workshops held at the 39th Annual AAAI Conference on Artificial Intelligence (AAAI 2025). In this second round-up article, we hear from the organisers of the workshops on:


Open Source AI for Mainstream Use
By Peter Santhanam

Chair organizer: Peter Santhanam
Program committee: Alexandru Cioba, James Hendler, Serdar Kadioglu, Ezequiel Lanza, Greg Lindahl, Sujee Maniyam, Manish Parashar, Pushkar Singh, Jonathan Starr, Raphaël Vienne

The first ever workshop on “Open Source AI for Mainstream Use” was held on March 4, 2025 at the Pennsylvania Convention Center in Philadelphia. The goal of this workshop was to bring the researchers and practitioners into a single forum to discuss topics at the intersection of AI and open source and demonstrate relevant technology.

Overall, the participants appreciated the interdisciplinary nature of this workshop and are looking forward to repeating it next year.


FLUID: Federated Learning for Unbounded and Intelligent Decentralization
By Daniela Annunziata and Marzia Canzaniello

Organisers: David Camacho, Diletta Chiaro, Francesco Picciali, Shadi Albarqouni
Chairs: Daniela Annunziata, Marzia Canzaniello

This first edition of the FLUID workshop focused on the emerging challenges and opportunities in federated learning and intelligent decentralization, bringing together a growing international community of researchers working across optimization, privacy, scalability, and practical deployment of decentralized learning systems.

Workshop chairs Marzia Canzaniello and Daniela Annunziata.

Real-world deployment challenges in federated learning were explored in the keynote by Holger Roth (NVIDIA), who discussed the gap between theoretical models and their application in real-world settings. His talk emphasized the practical complexities faced in deploying privacy-preserving systems at scale and sparked productive discussion among attendees.

Yang Liu’s keynote (Tsinghua University) introduced new perspectives on collaborative training across heterogeneous models, highlighting novel techniques for integrating large and small models in federated settings. His talk underlined the importance of designing flexible learning frameworks that can adapt to diverse client capabilities and data distributions.

Keynote speakers Yang Liu and Holger Roth.

The workshop showcased a broad spectrum of research topics, ranging from efficient communication and split learning architectures to applications in smart cities and medical diagnostics. This thematic diversity reflects the rapid evolution of the field and the critical role of interdisciplinary collaboration in addressing the technical and ethical dimensions of decentralized learning.

You can read this summary in a newspaper-style format here.


You can find the first article in this series here:

Fish AI Reader

Fish AI Reader

AI辅助创作,多种专业模板,深度分析,高质量内容生成。从观点提取到深度思考,FishAI为您提供全方位的创作支持。新版本引入自定义参数,让您的创作更加个性化和精准。

FishAI

FishAI

鱼阅,AI 时代的下一个智能信息助手,助你摆脱信息焦虑

联系邮箱 441953276@qq.com

相关标签

AAAI 2025 开放AI 联邦学习 人工智能
相关文章