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MikeDoes 
posted an update about 1 month ago
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Building powerful multilingual AI shouldn't mean sacrificing user privacy.

We're highlighting a solution-oriented report from researchers Sahana Naganandh, Vaibhav V, and Thenmozhi M at Vellore Institute of Technology that investigates this exact challenge. The direct connection to our mission is clear: the paper showcases the PII43K dataset as a privacy-preserving alternative to high-risk, raw multilingual data

The report notes that our dataset, with its structured anonymization, is a "useful option for privacy-centric AI applications." It's always a delight when academic research independently validates our data-first approach to solving real-world privacy problems.

This is how we build a safer AI future together.

🔗 Read the full report here to learn more: https://assets.cureusjournals.com/artifacts/upload/technical_report/pdf/3689/20250724-59151-93w9ar.pdf

🚀 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

Please guys work upon making ai model safe, and research on protecting open source ai models from jailbreaking that would help the ai community a lot, you can read my article here: Steering, Not Censoring: A Benchmark Suite for Safe and Creative Open-Source AI https://share.google/NeKrAQEGMeeM0xBrY