"Addressing GenAI Resilience and Security in Fully/GenAI Automated Cloud Environments" focuses on strengthening the resilience of AI-driven cloud ecosystems. As Generative AI automates critical operations, ensuring adaptability against failures, cyber threats, and adversarial AI attacks is paramount. This session explores strategies for building self-healing AI infrastructures, securing AI supply chains, and mitigating model drift. Key topics include fault-tolerant AI architectures, automated recovery mechanisms, and continuous monitoring for AI integrity. Attendees will gain insights into enhancing AI robustness, ensuring compliance, and maintaining operational continuity in dynamic cloud environments. This discussion is essential for professionals aiming to fortify AI ecosystems against evolving threats while sustaining performance and reliability.
Learning Objectives:
Understand the key challenges in ensuring resilience and security in GenAI-driven cloud environments and implement fault-tolerant AI architectures and self-healing mechanisms to enhance system reliability.
Mitigate risks related to AI model drift, adversarial attacks, and supply chain vulnerabilities, leverage automated monitoring and recovery strategies to sustain AI integrity and operational continuity.
Apply best practices for securing AI pipelines while maintaining compliance and governance.