The Temperature Feature of ChatGPT: Modifying Creativity for Clinical Research
Autor: | Joshua Davis, Liesbet Van Bulck, Brigitte N Durieux, Charlotta Lindvall |
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Jazyk: | angličtina |
Rok vydání: | 2024 |
Předmět: | |
Zdroj: | JMIR Human Factors, Vol 11, p e53559 (2024) |
Druh dokumentu: | article |
ISSN: | 2292-9495 58980342 |
DOI: | 10.2196/53559 |
Popis: | More clinicians and researchers are exploring uses for large language model chatbots, such as ChatGPT, for research, dissemination, and educational purposes. Therefore, it becomes increasingly relevant to consider the full potential of this tool, including the special features that are currently available through the application programming interface. One of these features is a variable called temperature, which changes the degree to which randomness is involved in the model’s generated output. This is of particular interest to clinicians and researchers. By lowering this variable, one can generate more consistent outputs; by increasing it, one can receive more creative responses. For clinicians and researchers who are exploring these tools for a variety of tasks, the ability to tailor outputs to be less creative may be beneficial for work that demands consistency. Additionally, access to more creative text generation may enable scientific authors to describe their research in more general language and potentially connect with a broader public through social media. In this viewpoint, we present the temperature feature, discuss potential uses, and provide some examples. |
Databáze: | Directory of Open Access Journals |
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