This editorial explores the advancements in generative artificial intelligence, focusing on the recently released OpenAI o1-Preview and its comparison to the traditional ChatGPT (GPT-4) model, particularly in the healthcare sector. While ChatGPT has shown significant applications in general medical advice and patient interactions, the o1-Preview introduces advanced reasoning capabilities through a "chain of thought" process, enabling it to handle more complex medical queries such as genetic disease discovery, multi-system disease care, and medical research support. The article highlights the potential benefits of the o1-Preview, including reduced hallucinations and more accurate outputs for complex medical problems, while also addressing ethical challenges, data diversity, access equity, and transparency. The editorial advocates for collaborative exploration of large language models (LLMs), including the o1-Preview, to fully leverage their transformative potential in medicine and healthcare delivery. By optimizing the use of both models, healthcare systems can enhance efficiency, precision, and patient outcomes, while mitigating previous LLM challenges. The authors conclude by emphasizing the need for further research and exploration to ensure the responsible integration of AI into medical practice.This editorial explores the advancements in generative artificial intelligence, focusing on the recently released OpenAI o1-Preview and its comparison to the traditional ChatGPT (GPT-4) model, particularly in the healthcare sector. While ChatGPT has shown significant applications in general medical advice and patient interactions, the o1-Preview introduces advanced reasoning capabilities through a "chain of thought" process, enabling it to handle more complex medical queries such as genetic disease discovery, multi-system disease care, and medical research support. The article highlights the potential benefits of the o1-Preview, including reduced hallucinations and more accurate outputs for complex medical problems, while also addressing ethical challenges, data diversity, access equity, and transparency. The editorial advocates for collaborative exploration of large language models (LLMs), including the o1-Preview, to fully leverage their transformative potential in medicine and healthcare delivery. By optimizing the use of both models, healthcare systems can enhance efficiency, precision, and patient outcomes, while mitigating previous LLM challenges. The authors conclude by emphasizing the need for further research and exploration to ensure the responsible integration of AI into medical practice.