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DIY AI

DIY AI

Dec 04, 20251 min read

tags
  • project

Table of Contents

  • DIY AI Motivation
  • DIY AI Research Questions
  • DIY AI Related Work
  • DIY AI Methods
  • DIY AI Findings RQ1
  • DIY AI Findings RQ2
  • DIY AI Findings RQ3 v1
  • DIY AI Findings RQ3 v2
  • DIY AI Posts RQ3
  • DIY AI Codebook RQ3
  • DIY AI Timeline
  • Defining open AI systems
  • Three levers of control, six levels of transparency

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Backlinks

  • Refusal in Language Models Is Mediated by a Single Direction
  • The Brief and Wondrous Life of Open Models
  • Near to Mid-term Risks and Opportunities of Open-Source Generative AI
  • Risks and Opportunities of Open-Source Generative AI
  • How Open Source Machine Learning Software Shapes AI
  • Opening up ChatGPT: Tracking openness, transparency, and accountability in instruction-tuned text generators
  • Rethinking open source generative AI: open-washing and the EU AI Act
  • AI as a Sport: On the Competitive Epistemologies of Benchmarking
  • The AI community building the future? A quantitative analysis of development activity on Hugging Face Hub
  • Why Companies "Democratise" Artificial Intelligence: The Case of Open Source Software Donations
  • Opening the Scope of Openness in AI
  • Crowdsourcing Scientific Software Documentation: A Case Study of the NumPy Documentation Project
  • Democratising AI: Multiple Meanings, Goals, and Methods
  • Open-Sourcing Highly Capable Foundation Models: An evaluation of risks, benefits, and alternative methods for pursuing open-source objectives
  • Navigating Uncertainties: Understanding How GenAI Developers Document Their Models on Open-Source Platforms
  • The Model Openness Framework: Promoting Completeness and Openness for Reproducibility, Transparency, and Usability in Artificial Intelligence
  • Limits and Possibilities for “Ethical AI” in Open Source: A Study of Deepfakes
  • Open (For Business): Big Tech, Concentrated Power, and the Political Economy of Open AI
  • Magnet or sticky? an OSS project-by-project typology
  • Controlling Large Language Models Through Concept Activation Vectors
  • Welcome

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