Curiosity serves as a pivotal conduit for human beings to discover and learn new knowledge. Recent advancements of large language models (LLMs) in natural language processing have sparked discussions regarding whether these models possess capability of curiosity-driven learning akin to humans. In this paper, starting from the human curiosity assessment questionnaire Five-Dimensional Curiosity scale Revised (5DCR), we design a comprehensive evaluation framework that covers dimensions such as Information Seeking, Thrill Seeking, and Social Curiosity to assess the extent of curiosity exhibited by LLMs. The results demonstrate that LLMs exhibit a stronger thirst for knowledge than humans but still tend to make conservative choices when faced with uncertain environments. We further investigated the relationship between curiosity and thinking of LLMs, confirming that curious behaviors can enhance the model's reasoning and active learning abilities. These findings suggest that LLMs have the potential to exhibit curiosity similar to that of humans, providing experimental support for the future development of learning capabilities and innovative research in LLMs.

Artificial intelligence (AI) is an excellent and rapidly growing field that involves the development of algorithms and systems that continuously tend to perform tasks that typically require human intelligence. AI systems can process vast amounts of data, identify patterns, make predictions and automate repetitive tasks. Recent years have seen a rapid advancement in AI capabilities, resulting in its adoption across various manufacturing and finance industries. Despite the impressive capabilities of AI, it is essential to recognize that it still has limitations. While AI systems can process vast amounts of data and make predictions, they need more independent thought and creativity, often essential for scientific exploration and discovery.

Curiosity Artificial Intelligence also known as curiosity AI, artificial curiosity, AI curiosity, curious algorithm and algorithmic curiosity is the simulation of human curiosity in Artificial intelligence. If we take humans as an example, curiosity is what makes us learn things. Starting from a stage when humans get maturity, he/she becomes curious about the movements around them and learns from it. Then think about AI getting curious. AI is already known for its features that have reached the cliff by its technological improvements.

Curiosity Artificial Intelligence also known as curiosity AI, artificial curiosity, AI curiosity, curious algorithm and algorithmic curiosity is the simulation of human curiosity in Artificial intelligence. If we take humans as an example, curiosity is what makes us learn things. Starting from a stage when humans get maturity, he/she becomes curious about the movements around them and learns from it. Then think about AI getting curious. AI is already known for its features that have reached the cliff by its technological improvements.

Curiosity has been hailed as one of the most critical competencies for the modern workplace. Countries with higher curiosity enjoy more economic and political freedom, as well as higher GDPs. It is therefore not surprising that, as future jobs become less predictable, a growing number of organizations will hire individuals based on what they could learn, rather than on what they already know. Of course, people's careers are still largely dependent on their academic achievements, which are (at least partly) a result of their curiosity. Since no skill can be learned without a minimum level of interest, curiosity may be considered one of the critical foundations of talent.