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Building a Responsible and Open
Community for Generative AI

The LF AI & Data Generative AI Commons is dedicated to fostering 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.

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Our Workstreams

The Generative AI Commons is a community-driven open membership initiative with elected chairs and represented by non-profits, academia and industry in a neutral forum. We embrace responsible and trustworthy AI, foster collaboration, promote AI literacy and advocate for our community.

Models, Applications & Data Workstream

  • Building a GenAI landscape 
  • Build GenAI solution stack/reference architecture/ecosystem
  • Identify open source projects in the MAD area for LF AI & Data
  • Host open discussions and build thought leadership in the MAD area
  • Support LF AI & Data GenAI projects/help grow ecosystem if needed

Frameworks Workstream

Education and Outreach Workstream

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

Responsible AI Workstream

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

Workstream Leaders

Anni Lai

Generative AI Commons Chair

Arnaud Le Hors

Generative AI Commons Vice Chair

Ahmed Abdelmonsef

Framework Workstream Lead

Alexy Khrabrov

Framework Workstream Lead

Nick Chase

Model and Data Workstream Lead

Sriram Easwaran

Model and Data Workstream Lead

Sachin Varghese

Applications Workstream Lead

Raghavan Muthuregunathan

Applications Workstream Lead & Education and Outreach Workstream Lead

Susan Malaika

Responsible AI Workstream Lead

Suparna Bhattacharya

Responsible AI Workstream Lead

Ofer Hermoni

Education and Outreach Workstream Lead

Projects

We host open source projects that drive generative AI innovation across industries in an ethically responsible way, from models and datasets to vector stores and AI application frameworks.

We encourage the publishing of data sets, and models including source code with weights and biases released under open-source licenses. We promote transparency and recommend that research papers be informal and discuss possible harms and the means to mitigate them.

We are backed by a global community of AI researchers, engineers, data scientists, ethicists and developers and we provide resources and accessible tools that are designed to foster collaboration and empower developers to innovate and build with generative AI while embracing the tenants of Responsible AI.

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Get Involved

The Generative AI Commons, an initiative of the LF AI & Data Foundation, democratizes generative AI by hosting open-source models, datasets, and applications. We publish standards and frameworks to support interoperability and economies of scale.

Collaborating with industry leaders, researchers, and policymakers, we promote Responsible AI principles for open-source AI and open science. Our goal is to ensure ethical, transparent, and accountable AI practices that benefit enterprises, industries, non-profits, academia, and humanity.

We advance AI literacy and Responsible AI through education and training programs, helping the community and public understand the benefits and risks of generative AI.

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