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Stable Attribution

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Stable Attribution is an AI tool that specializes in generating unique and authentic images through Stable Diffusion, with the ability to analyze and track the performance of the generated images and provide attribution to the creators


  • 😊 User-Friendly Interface: Stable Attribution offers a user-friendly interface for easy navigation and use.
  • 📊 Data Visualization: The platform provides robust data visualization tools to effectively present and analyze attribution data.
  • 🔄 Attribution Tracking: Stable Attribution enables comprehensive tracking of attribution data, allowing users to monitor and analyze various attribution sources.
  • 📈 Performance Analysis: Users can conduct in-depth performance analysis of their marketing and advertising efforts through the platform’s features.
  • 🛡️ Security Measures: The platform implements robust security measures to ensure the confidentiality and integrity of the attribution data.
Tech Used
Chakra UI, Tailwind CSS, Node.js, React, Emotion, Next.js, Next.js

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Stable Attribution was built by Jeff Huber and Anton Troynikov, with the help and feedback of many others. The project was initiated at Chroma, a startup founded to make AI understandable by analyzing how the data used to train models influences their behavior.
The purpose of Stable Attribution is to provide attribution information for AI-generated images, helping users understand the sources of images and giving credit to the contributing artists.
Users can contribute to Stable Attribution by providing feedback on the attribution results, helping to improve the algorithm and provide better credit to artists.

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