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Building on HF
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Michael Anthony
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MikeDoes
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http://www.ai4privacy.com
MikeDoesDo
MikeDoes
AI & ML interests
Privacy, Large Language Model, Explainable
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A single lock on a door isn't enough. Real security is about layers. The same is true for AI privacy. A new paper, "Whispered Tuning", offers a fantastic layered solution that aims to fortify LLMs against privacy infringements. We're proud that the first, essential layer, a high-precision PII redaction model was built on the foundation of the Ai4Privacy/pii-65k dataset. Our dataset provided the necessary training material for their initial anonymization step, which then enabled them to develop further innovations like differential privacy fine-tuning and output filtering. This is a win-win: our data helps create a solid base, and researchers build powerful, multi-stage privacy architectures on top of it. Together, we're making AI safer. ๐ Read the full paper to see how a strong foundation enables a complete privacy solution: https://www.scirp.org/journal/paperinformation?paperid=130659 ๐ Stay updated on the latest in privacy-preserving AIโfollow us on LinkedIn: https://www.linkedin.com/company/ai4privacy/posts/
reacted
to
their
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with ๐ง
about 8 hours ago
A single lock on a door isn't enough. Real security is about layers. The same is true for AI privacy. A new paper, "Whispered Tuning", offers a fantastic layered solution that aims to fortify LLMs against privacy infringements. We're proud that the first, essential layer, a high-precision PII redaction model was built on the foundation of the Ai4Privacy/pii-65k dataset. Our dataset provided the necessary training material for their initial anonymization step, which then enabled them to develop further innovations like differential privacy fine-tuning and output filtering. This is a win-win: our data helps create a solid base, and researchers build powerful, multi-stage privacy architectures on top of it. Together, we're making AI safer. ๐ Read the full paper to see how a strong foundation enables a complete privacy solution: https://www.scirp.org/journal/paperinformation?paperid=130659 ๐ Stay updated on the latest in privacy-preserving AIโfollow us on LinkedIn: https://www.linkedin.com/company/ai4privacy/posts/
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2 days ago
A single lock on a door isn't enough. Real security is about layers. The same is true for AI privacy. A new paper, "Whispered Tuning", offers a fantastic layered solution that aims to fortify LLMs against privacy infringements. We're proud that the first, essential layer, a high-precision PII redaction model was built on the foundation of the Ai4Privacy/pii-65k dataset. Our dataset provided the necessary training material for their initial anonymization step, which then enabled them to develop further innovations like differential privacy fine-tuning and output filtering. This is a win-win: our data helps create a solid base, and researchers build powerful, multi-stage privacy architectures on top of it. Together, we're making AI safer. ๐ Read the full paper to see how a strong foundation enables a complete privacy solution: https://www.scirp.org/journal/paperinformation?paperid=130659 ๐ Stay updated on the latest in privacy-preserving AIโfollow us on LinkedIn: https://www.linkedin.com/company/ai4privacy/posts/
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Terminal Visualiser
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Create and download styled terminal screenshots
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Visualize workflows from TSV data