Small Language Models (SLMs) provide a viable alternative to Large Language Models (LLMs) for developing high-performing, cost-effective, and secure generative AI solutions. CDAOs, AI architects, and data architects should attend this presentation to gain insights into the strengths and weaknesses of SLMs and discover five specific use cases where SLMs outperform LLMs.

In this session, we will explore cost transformative vendors such as DeepSeek and MistralAI’s impact on AI development, highlighting the potential to enhance enterprise innovation at a price/performance that is unprecedented. Data, analytics & AI leaders can bring their questions on how they can capitalize on new training and inferencing paradigms in AI, the future of AI model development and the impact of reasoning models on a more autonomous future in AI.

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.