Generative AI (GenAI) has significantly improved our daily lives, prompting a focus on its integration into products and our routines. However, the growing importance of GenAI brings along significant concerns regarding privacy and vulnerability.

This talk delves into the critical issues surrounding the protection of private data and the security of GenAI systems. We'll begin by understanding the fundamental differences between data privacy and data security. Drawing insights from real-life data breaches and compromised information in major companies, we'll explore the mistakes made and the steps taken to rectify them. Throughout the discussion, we'll analyze the challenges faced by GenAI in ensuring data privacy and security across various stages of an LLM project.

Furthermore, the talk will shed light on how prominent companies building GenAI are working to reduce the impact of data privacy and security concerns within their models. Additionally, we'll explore strategies for individuals, like ourselves, using GenAI, to enhance data privacy and security when integrating it into our products or daily lives. Finally, the role and significance of government regulations in ensuring the safety and security of GenAI will be emphasized.

John Robert

John Robert is a Senior Machine Learning Engineer at Condo GMBH, boasting five years of expertise in machine learning. Their focus lies in deploying models while prioritizing data privacy and security. With prior experience at Daimler (Mercedes Benz) and Bosch Autonomous Driving, Robert has a rich background in automotive AI.

Passionate about innovation, Robert actively participates in Hackathons and is a valued member of the MLOps community, contributing to advancements in AI technology and fostering collaboration.