How AI prompting shapes accuracy, efficiency and cost
Goldie Negelev
New UC Berkeley research maps how AI reasoning strategies affect accuracy, efficiency As large language models (LLMs) move from research labs into classrooms, offices and engineering workflows, “prompt engineering” has become a central practice for shaping how LLMs reason and respond. A new study led by UC Berkeley researchers goes beyond the general understanding that… The post How AI prompting shapes accuracy, efficiency and cost appeared first on UC Berkeley IEOR Department - Industrial Engin