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Waypoint-1.5: Higher-Fidelity Interactive Worlds for Everyday GPUs ALTK‑Evolve: On‑the‑Job Learning for AI Agents Safetensors is Joining the PyTorch Foundation Holo3: Breaking the Computer Use Frontier Any Custom Frontend with Gradio's Backend A New Framework for Evaluating Voice Agents (EVA) Bringing Robotics AI to Embedded Platforms: Dataset Recording, VLA Fine‑Tuning, and On‑Device Optimizations One-Shot Any Web App with Gradio's gr.HTML CUGA on Hugging Face: Democratizing Configurable AI Agents New in llama.cpp: Model Management Building Deep Research: How we Achieved State of the Art OVHcloud on Hugging Face Inference Providers 🔥 20x Faster TRL Fine-tuning with RapidFire AI Building for an Open Future - our new partnership with Google Cloud Aligning to What? Rethinking Agent Generalization in MiniMax M2 Building a Healthcare Robot from Simulation to Deployment with NVIDIA Isaac Sentence Transformers is joining Hugging Face! 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AI Policy @🤗: Open ML Considerations in the EU AI Act
Yacine Jernite · 2023-07-24 · via Hugging Face - Blog

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Yacine Jernite's avatar

Like everyone else in Machine Learning, we’ve been following the EU AI Act closely at Hugging Face. It’s a ground-breaking piece of legislation that is poised to shape how democratic inputs interact with AI technology development around the world. It’s also the outcome of extensive work and negotiations between organizations representing many different components of society – a process we’re particularly sensitive to as a community-driven company. In the present position paper written in coalition with Creative Commons, Eleuther AI, GitHub, LAION, and Open Future, we aim to contribute to this process by sharing our experience of the necessary role of open ML development in supporting the goals of the Act – and conversely, by outlining specific ways in which the regulation can better account for the needs of open, modular, and collaborative ML development.

Hugging Face is where it is today thanks to its community of developers, so we’ve seen firsthand what open development brings to the table to support more robust innovation for more diverse and context-specific use cases; where developers can easily share innovative new techniques, mix and match ML components to suit their own needs, and reliably work with full visibility into their entire stack. We’re also acutely aware of the necessary role of transparency in supporting more accountability and inclusivity of the technology – which we’ve worked on fostering through better documentation and accessibility of ML artifacts, education efforts, and hosting large-scale multidisciplinary collaborations, among others. Thus, as the EU AI Act moves toward its final phase, we believe accounting for the specific needs and strengths of open and open-source development of ML systems will be instrumental in supporting its long-term goals. Along with our co-signed partner organizations, we make the following five recommendations to that end:

  1. Define AI components clearly,
  2. Clarify that collaborative development of open source AI components and making them available in public repositories does not subject developers to the requirements in the AI Act, building on and improving the Parliament text’s Recitals 12a-c and Article 2(5e),
  3. Support the AI Office’s coordination and inclusive governance with the open source ecosystem, building on the Parliament’s text,
  4. Ensure the R&D exception is practical and effective, by permitting limited testing in real-world conditions, combining aspects of the Council’s approach and an amended version of the Parliament’s Article 2(5d),
  5. Set proportional requirements for “foundation models,” recognizing and distinctly treating different uses and development modalities, including open source approaches, tailoring the Parliament’s Article 28b.

You can find more detail and context for those in the full paper here!