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Data Privacy

A collection of 4 posts

State of Text2SQL 2024

State of Text2SQL 2024

Text to SQL is a task that aims to convert natural language questions into corresponding SQL queries that can be executed in relational databases. Interestingly, this problem statement has been through research before the rise of Large Language Models.

LLM Datasets and Contamination

LLM Datasets and Contamination

Prem AI's post addresses dataset contamination in LLM training, where overlap between training and test sets inflates performance. It explores detection methods, data curation best practices, and ethical concerns around mislabeled or duplicated content.

The Synthetic Data Revolution

The Synthetic Data Revolution

This article delves into the emergence of synthetic data in AI, discussing its generation methods, applications across various data types, and its significance in overcoming data scarcity and privacy challenges, ultimately contributing to the pursuit of Artificial General Intelligence (AGI)

RAGs are cool, but what about their privacy?

RAGs are cool, but what about their privacy?

This article explores privacy concerns in Retrieval-Augmented Generation (RAG) applications, highlighting data protection challenges and offering actionable solutions to ensure secure and compliant AI systems while leveraging the benefits of RAG.