inclusionAI/ZwZ-8B
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MikeDoes's
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How do you prove a new AI privacy tool actually works? You test it against a world-class benchmark.
That's why we're proud our data played a key role in the research for "Rescriber," a new browser extension for user-led anonymization. To objectively measure their tool's performance against other methods, the researchers needed a diverse and challenging evaluation set.
They built their benchmark using 240 samples from the Ai4Privacy open dataset.
This is a win-win for the ecosystem: our open-source data helps researchers validate their innovative solutions, and in turn, their work pushes the entire field of privacy-preserving AI forward. The "Rescriber" tool is a fantastic step towards on-device, user-controlled privacy.
🔗 Learn more about their data-driven findings in the full paper: https://arxiv.org/pdf/2410.11876
🚀 Stay updated on the latest in privacy-preserving AI—follow us on LinkedIn: https://www.linkedin.com/company/ai4privacy/posts/
#DataPrivacy #AI #OpenSource #Anonymization #MachineLearning #HealthcareAI #Ai4Privacy
That's why we're proud our data played a key role in the research for "Rescriber," a new browser extension for user-led anonymization. To objectively measure their tool's performance against other methods, the researchers needed a diverse and challenging evaluation set.
They built their benchmark using 240 samples from the Ai4Privacy open dataset.
This is a win-win for the ecosystem: our open-source data helps researchers validate their innovative solutions, and in turn, their work pushes the entire field of privacy-preserving AI forward. The "Rescriber" tool is a fantastic step towards on-device, user-controlled privacy.
🔗 Learn more about their data-driven findings in the full paper: https://arxiv.org/pdf/2410.11876
🚀 Stay updated on the latest in privacy-preserving AI—follow us on LinkedIn: https://www.linkedin.com/company/ai4privacy/posts/
#DataPrivacy #AI #OpenSource #Anonymization #MachineLearning #HealthcareAI #Ai4Privacy
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