Comparative analysis of large language models in the Royal College of Ophthalmologists fellowship exams

Recent years have witnessed an increasing interest in the application of Artificial Intelligence (AI) and deep learning in Ophthalmology [ 1 ]. Large language models (LLMs) have become a popular area of research in this field, and have been integrated into publicly available chatbots such as ChatGPT 3.5 and 4.0 ( OpenAI , CA, US), Google Bard ( Alphabet Inc ., CA, US), and Bing Chat ( Microsoft Corporation , WA, US) [ 2 , 3 , 4 , 5 ]. LLMs have been trained on vast amounts of data, enabling them to generate human-like text and answer complex questions. This capability has the potential to revolutionise clinical practice and assessment [ 2 , 6 , 7 ].