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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 2 hours ago
We can't build more private AI if we can't measure privacy intelligence. That's why we're highlighting the Priv-IQ benchmark, a new, solution-oriented framework for evaluating LLMs on eight key privacy competencies, from visual privacy to knowledge of privacy law. The direct connection to our work is clear: the researchers relied on samples from the Ai4Privacy dataset to build out questions for Privacy Risk Assessment and Multilingual Entity Recognition. This is the power of open-source collaboration. We provide the data building blocks, and researchers construct powerful new evaluation tools on top of them. It's a win-win for the entire ecosystem when we can all benefit from transparent, data-driven benchmarks that help push for better, safer AI. Kudos to Sakib Shahriar and Rozita A. Dara for this important contribution. Read the paper to see the results: https://www.proquest.com/docview/3170854914?pq-origsite=gscholar&fromopenview=true&sourcetype=Scholarly%20Journals #OpenSource #DataPrivacy #LLM #Anonymization #AIsecurity #HuggingFace #Ai4Privacy #Worldslargestopensourceprivacymaskingdataset
reacted to their post with 👀 about 2 hours ago
Traditional data leak prevention is failing. A new paper has a solution-oriented approach inspired by evolution. The paper introduces a genetic-algorithm-driven method for detecting data leaks. To prove its effectiveness, the researchers Anatoliy Sachenko, Petro V., Oleg Savenko, Viktor Ostroverkhov, Bogdan Maslyyak from Casimir Pulaski Radom University and others needed a real-world, complex PII dataset. We're proud that the AI4Privacy PII 300k dataset was used as a key benchmark for their experiments. This is the power of open-source collaboration. We provide complex, real-world data challenges, and brilliant researchers develop and share better solutions to solve them. It's a win for every organization when this research helps pave the way for more adaptive and intelligent Data Loss Prevention systems. 🔗 Read the full paper to see the data and learn how genetic algorithms are making a difference in cybersecurity: https://ceur-ws.org/Vol-4005/paper19.pdf #OpenSource #DataPrivacy #LLM #Anonymization #AIsecurity #HuggingFace #Ai4Privacy #Worldslargestopensourceprivacymaskingdataset
posted an update 1 day ago
We can't build more private AI if we can't measure privacy intelligence. That's why we're highlighting the Priv-IQ benchmark, a new, solution-oriented framework for evaluating LLMs on eight key privacy competencies, from visual privacy to knowledge of privacy law. The direct connection to our work is clear: the researchers relied on samples from the Ai4Privacy dataset to build out questions for Privacy Risk Assessment and Multilingual Entity Recognition. This is the power of open-source collaboration. We provide the data building blocks, and researchers construct powerful new evaluation tools on top of them. It's a win-win for the entire ecosystem when we can all benefit from transparent, data-driven benchmarks that help push for better, safer AI. Kudos to Sakib Shahriar and Rozita A. Dara for this important contribution. Read the paper to see the results: https://www.proquest.com/docview/3170854914?pq-origsite=gscholar&fromopenview=true&sourcetype=Scholarly%20Journals #OpenSource #DataPrivacy #LLM #Anonymization #AIsecurity #HuggingFace #Ai4Privacy #Worldslargestopensourceprivacymaskingdataset
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