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Michael Anthony PRO

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http://www.aisuisse.com

AI & ML interests

Privacy, Large Language Model, Explainable

Recent Activity

reacted to their post with 👀 about 6 hours ago
The future of AI privacy isn't just in the cloud; it's on your device. But how do we build and validate these tools? A new paper on "Rescriber" explores this with a tool that uses smaller LLMs for on-device anonymization. Building and validating such tools requires a strong data foundation. We're excited to see that the researchers used the Ai4Privacy open dataset to create their performance benchmarks. This is our mission in action: providing the open-source data that helps innovators build and test better solutions that will give users more control over their privacy. It's a win for the community when our data helps prove the feasibility of on-device AI for data minimization, with reported user perceptions on par with state-of-the-art cloud models. Shoutout to Jijie Zhou, Eryue Xu, Yaoyao Wu, and Tianshi Li on this one! 🔗 Check out the research to see how on-device AI, powered by solid data, is changing the game: https://dl.acm.org/doi/pdf/10.1145/3706598.3713701 🚀 Stay updated on the latest in privacy-preserving AI—follow us on LinkedIn: https://www.linkedin.com/company/ai4privacy/posts/ #OpenSource #DataPrivacy #LLM #Anonymization #AIsecurity #HuggingFace #Ai4Privacy #Worldslargestopensourceprivacymaskingdataset
reacted to their post with 🚀 1 day ago
Why choose between performance, privacy, and transparency when you can have all three? We're highlighting a solution-oriented paper that introduces PRvL, an open-source toolkit for PII redaction. The interesting part, the researchers used the AI4Privacy-300K and AI4Privacy-500K datasets to train and benchmark their suite of models. This is the power of open-source collaboration. We provide the comprehensive data foundation, and the community builds better solutions on top of it. It's a win for every organization when this research results in a powerful, free, and self-hostable tool that helps keep their data safe. Big cheers to Leon Garza, Anantaa Kotal, Aritran Piplai, Lavanya Elluri, Prajit D., and Aman Chadha for pulling this off. 🔗 Read the full paper to see their data-driven results and access the PRvL toolkit: https://arxiv.org/pdf/2508.05545 🚀 Stay updated on the latest in privacy-preserving AI—follow us on LinkedIn: https://www.linkedin.com/company/ai4privacy/posts/ #OpenSource #DataPrivacy #LLM #Anonymization #AIsecurity #HuggingFace #Ai4Privacy #Worldslargestopensourceprivacymaskingdataset
posted an update 1 day ago
Why choose between performance, privacy, and transparency when you can have all three? We're highlighting a solution-oriented paper that introduces PRvL, an open-source toolkit for PII redaction. The interesting part, the researchers used the AI4Privacy-300K and AI4Privacy-500K datasets to train and benchmark their suite of models. This is the power of open-source collaboration. We provide the comprehensive data foundation, and the community builds better solutions on top of it. It's a win for every organization when this research results in a powerful, free, and self-hostable tool that helps keep their data safe. Big cheers to Leon Garza, Anantaa Kotal, Aritran Piplai, Lavanya Elluri, Prajit D., and Aman Chadha for pulling this off. 🔗 Read the full paper to see their data-driven results and access the PRvL toolkit: https://arxiv.org/pdf/2508.05545 🚀 Stay updated on the latest in privacy-preserving AI—follow us on LinkedIn: https://www.linkedin.com/company/ai4privacy/posts/ #OpenSource #DataPrivacy #LLM #Anonymization #AIsecurity #HuggingFace #Ai4Privacy #Worldslargestopensourceprivacymaskingdataset
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Organizations

Ai4Privacy's profile picture Social Post Explorers's profile picture Mistral AI Game Jam's profile picture AI STATUS CODES's profile picture Swiss {ai} Weeks's profile picture