Securing and derisking AI requires new processes, tools and mindsets. Risks abound internally and externally while regulations take hold. This session outlines frameworks, tools and processes for managing AI trust, risk and security.

AI systems can have significant impact in organizations decisions and product offerings. This has triggered a complex regulatory landscape and related organizational guidance to ensure responsible and ethical implementation of AI systems. This session provides the technology framework supporting the processes and policies for a reliable AI system that is fair, safe and secure.

Despite the popularity of retrieval-augmented generation, organizations are struggling to optimize large language model applications based on RAG. Attend this session to get suggestions and recommendations on improving your RAG solution, LLMOps for RAG systems, and scaling considerations.