Generative AI, particularly Large Language Models (LLMs), is rapidly becoming key to enterprise and cross-industry applications. LLMs have versatile applications including:

  • Text generation
  • Natural language understanding
  • Conversational dialog, code generation
  • Emerging multi-modal capabilities

The LF AI & Data Generative AI Commons is committed to promoting the democratization, advancement, and adoption of efficient, secure, reliable, and ethical Generative AI open source innovations.

Through neutral governance, open and transparent collaboration, and education, the Generative AI Commons fosters open source and open-science principles. This initiative aims to create a neutral and inclusive community where organizations collaborate and contribute to developing enterprise-ready platforms, effectively filling a critical gap in the generative AI landscape.

Read more here.

Not-for-profit

A non-profit that hosts and promotes the collaborative development of open source projects (sw, hw, standards)

Neutral

Trusted neutral foundation hosting projects and their IP, encourages organizations to collaborate & contribute

Open Governance

Open, transparent and fair governance model across all efforts and projects

Credible

3000+ members, 900+ projects, leading OSS technologies in all sectors

 

Initial Gen AI Commons Workstreams

Models and Data Workstream

  • Host Ethical and Trustworthy Models
  • Host Ethical Data Sets and Processing Tools
  • Host Benchmarks and Publish Results
  • Assist Non-Profits in Securing Resources

Applications Workstream

  • Host AI Application Frameworks and Tools
  • Host Database Platforms (vector stores, graph)
  • Host Agent Application Frameworks
  • Publish Interface and Metadata Formats

Frameworks Workstream

  • Model Openness Framework and Report
  • Responsible AI Framework
  • Generative AI Reference Architectures
  • Develop Best Practices and Guidelines

Education and Outreach Workstream

  • Offer Generative AI Training and Certification
  • Provide Thought Leadership
  • Perform Academic and Member Outreach
  • Advocat for Open Source AI with Governments

Responsible AI Workstream

  • Responsible AI
  • Security, Privacy and Safety
  • Informing Policy
  • Copyright Issues
  • Model and Data Lineage

Landscape

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