分析ChatGPT作为提高业务操作效率和有效性的工具的潜在好处和用例

Rohit Raj , Arpit Singh , Vimal Kumar , Pratima Verma
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引用次数: 4

摘要

这项研究探讨了采用ChatGPT对公司的潜在好处,ChatGPT是一种流行的聊天机器人,建立在一种大规模的基于转换器的语言模型上,称为生成预训练转换器(GPT)。像ChatGPT这样的聊天机器人可以改善客户服务,同时处理多个客户查询,并节省运营成本。此外,ChatGPT可以自动化订单跟踪和计费等常规流程,使员工能够专注于更复杂和战略性的职责。尽管如此,在部署ChatGPT之前,企业必须仔细分析它的用例和限制,以及它的优势和劣势。例如,ChatGPT需要特定于业务领域的训练数据,这些数据可能会产生错误和模糊的结果。该研究通过借鉴目前在ChatGPT、大规模语言模型和人工智能上可以获得的文献,确定了ChatGPT在企业中可能带来的好处的部署领域。然后,使用PSI(偏好选择指数)和COPRAS(复杂比例评估)方法,将潜在优势考虑在内并排定优先级。通过强调行业的当前趋势和可能的优势,这篇社论试图深入了解在企业和研究中使用ChatGPT的现状。ChatGPT还可以从训练数据中学习偏见,并创建强化这些偏见的回复。因此,企业必须根据具体操作对ChatGPT进行培训和微调,为其使用设置明确的边界和限制,并实施适当的安全措施以避免恶意输入。该研究概述了ChatGPT对企业的潜在好处,分析了其优势和局限性,并深入了解了组织如何利用ChatGPT的能力来增强其运营,从而突出了缺乏文献的研究差距。
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Analyzing the potential benefits and use cases of ChatGPT as a tool for improving the efficiency and effectiveness of business operations

The study addresses the potential benefits for companies of adopting ChatGPT, a popular chatbot built on a large-scale transformer-based language model known as a generative pre-trained transformer (GPT). Chatbots like ChatGPT may improve customer service, handle several client inquiries at once, and save operational costs. Moreover, ChatGPT may automate regular processes like order tracking and billing, allowing human employees to focus on more complex and strategic responsibilities. Nevertheless, before deploying ChatGPT, enterprises must carefully analyze its use cases and restrictions, as well as its strengths and disadvantages. ChatGPT, for example, requires training data that is particular to the business domain and might produce erroneous and ambiguous findings. The study identifies areas of deployment of ChatGPT's possible benefits in enterprises by drawing on the literature that is currently accessible on ChatGPT, massive language models, and artificial intelligence. Then, using the PSI (Preference Selection Index) and COPRAS (Complex Proportional Assessment) approaches, potential advantages are taken into account and prioritized. By highlighting current trends and possible advantages in the industry, this editorial seeks to provide insight into the present state of employing ChatGPT in enterprises and research. ChatGPT may also learn biases from training data and create replies that reinforce those biases. As a result, enterprises must train and fine-tune ChatGPT to specific operations, set explicit boundaries and limitations for its use, and implement appropriate security measures to avoid malicious input. The study highlights the research gap in the dearth of literature by outlining ChatGPT's potential benefits for businesses, analyzing its strengths and limits, and offering insights into how organizations might use ChatGPT's capabilities to enhance their operations.

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