The widespread adoption of large language models (LLMs), such as OpenAI's ChatGPT, could revolutionize various industries, including geotechnical engineering. However, GPT models can sometimes generate plausible-sounding but false outputs, leading to hallucinations. In this article, we discuss the importance of prompt engineering in mitigating these risks and harnessing the full potential of GPT for geotechnical applications. We explore the challenges and pitfalls associated with LLMs and highlight the role of context in ensuring accurate and valuable responses. Furthermore, we examine the development of context-specific search engines and the potential of LLMs to become a natural interface for complex tasks, such as data analysis and design. We also develop a unified interface using natural language to handle complex geotechnical engineering tasks and data analysis. By integrating GPT into geotechnical engineering workflows, professionals can streamline their work and develop sustainable and resilient infrastructure systems for the future.
翻译:广泛应用大型语言模型(LLM),例如OpenAI的ChatGPT,可能会彻底改变各行各业,包括岩土工程。然而,GPT模型有时会产生听起来合理但是错误的输出,导致幻觉。在本文中,我们讨论了及时工程在减轻这些风险和发挥GPT在岩土应用中的全部潜力方面的重要性。我们探讨了与LLM相关的挑战和陷阱,并强调了上下文在确保准确和有价值的响应方面的作用。此外,我们还研究了开发上下文特定的搜索引擎的发展,以及LLM成为处理诸如数据分析和设计等复杂任务的自然接口的潜力。我们还使用自然语言开发了一个统一接口,用于处理复杂的岩土工程任务和数据分析。通过将GPT集成到岩土工程工作流程中,专业人士可以简化其工作,并为未来开发可持续和有弹性的基础设施系统。