Large language models (LLMs) are transforming various fields including healthcare, urban planning, chemistry, linguistics, humanities, and computer science, unlocking new scientific exploration opportunities. However, the rise of LLMs also presents significant challenges. This article addresses the state of LLM technology, outlining key obstacles and examining potential biases associated with its implementation. It highlights the pressing need for awareness regarding these pitfalls as LLMs become integrated into diverse domains. Furthermore, the discussion touches on emerging technologies like neuromorphic engineering, which promise to improve the energy efficiency of LLM deployment on hardware platforms. By focusing on both the benefits and challenges, this piece provides a comprehensive overview of how LLMs are reshaping science, emphasizing the importance of ethical considerations and sustainable practices in their use. Stay informed on the latest trends in LLM technology and its implications for various industries and academic disciplines.
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