About this talk
This talk addresses the evolving role of software developers in the age of AI, emphasizing the necessity for engineers to understand the foundational principles of AI architecture. The speaker explores the distinction between high-level prompt engineering and detailed data science, focusing on the nature of models as software artifacts and their execution through inference runtimes. By approaching models from an engineering perspective instead of a purely research-oriented view, attendees gain the vocabulary and technical expertise required to effectively collaborate with data scientists and navigate beyond simple API usage. This session is essential for those looking to develop scalable, cost-effective, and high-performance enterprise applications.
