Generative AI (GenAI) has shown immense potential in transforming various sectors, from healthcare to finance. However, its adoption at scale faces several challenges, including technical, ethical, regulatory, economic, and organizational hurdles. This paper explores these challenges and proposes prompt decomposition as a viable solution. By breaking down complex queries into more straightforward, manageable tasks, prompt decomposition can optimize resource utilization, improve transparency, and enhance the overall efficiency of GenAI systems. We also discuss other techniques that can facilitate the widespread adoption of GenAI.
Introduction
Generative AI (GenAI) models, such as GPT-4, have revolutionized how we approach complex problems in various fields. Despite their potential, scaling GenAI for broader applications presents significant challenges. This paper aims to identify these challenges and explore how prompt decomposition and other techniques can help overcome them.