Open Source in Finance Forum New York 2024

This talk will explore the critical role of MLSecOps in enhancing the security and trustworthiness of AI and machine learning systems, particularly in the context of open-source ML models and MLOps tools. As the use of open-source components grows across industries, organizations face increasing challenges in managing the security risks inherent in these technologies. D will discuss how MLSecOps integrates security throughout the AI/ML lifecycle, from development to deployment, ensuring that models and pipelines are resilient against emerging threats. Attendees will gain insights into best practices for securing open-source AI systems, the importance of maintaining a robust ML Bill of Materials (ML-BOM), and how leveraging MLSecOps practices can reduce vulnerabilities while accelerating innovation in AI. This session will focus on practical applications for using open-source tools and strategies to safeguard ML operations, empowering organizations to adopt open AI confidently.