The rapid emergence of new artificial intelligence tools has made it crucial for researchers to select appropriate large language models (LLMs) for specific tasks. From free chatbots to paid APIs and customizable downloads, the options are vast. Despite their impressive human-like responses, LLMs remain error-prone and require human oversight. OpenAI's latest models, particularly the o3 'reasoning model', demonstrate advanced problem-solving abilities, particularly in scientific and coding tasks. As competition grows, including from startups like DeepSeek, OpenAI has responded by enhancing its offerings to stay relevant in the field.
Researchers have more generative AI tools at their disposal than ever before, enabling them to edit manuscripts, write code, and generate hypotheses more efficiently.
While different LLMs excel at various tasks, they are still too error-prone to be fully relied upon independently, emphasizing the need for careful implementation.
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