Scholarlink

The increasing variety of generative AI systems and tools, particularly large language models, poses significant challenges for integration into larger software infrastructures due to issues with interoperability, scalability, and data protection. To address these challenges, this paper proposes a decentralised platform ecosystem that enables the composition of AI services from distributed data sources and models. The platform prioritises flexibility, scalability, re-usability, cooperation, and data protection, providing standardised interfaces and best practices for seamless collaboration among multiple stakeholders. By facilitating the creation of open, modular, and federated architectures, this ecosystem aims to unlock the full potential of AI in collaborative environments while ensuring secure data exchange and protecting sensitive information.

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Integrating Decentralised AI Services in a Collaboration Ecosystem

  • 会议论文

  • 发表日期：

    2026年

查看全文
  • Kerstin Sahler,
  • Tobias Hecking,
  • Thorsten Sommer,
  • Oliver Bensch

摘要

The increasing variety of generative AI systems and tools, particularly large language models, poses significant challenges for integration into larger software infrastructures due to issues with interoperability, scalability, and data protection. To address these challenges, this paper proposes a decentralised platform ecosystem that enables the composition of AI services from distributed data sources and models. The platform prioritises flexibility, scalability, re-usability, cooperation, and data protection, providing standardised interfaces and best practices for seamless collaboration among multiple stakeholders. By facilitating the creation of open, modular, and federated architectures, this ecosystem aims to unlock the full potential of AI in collaborative environments while ensuring secure data exchange and protecting sensitive information.