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高知特(Cognizant):2024边缘计算、AI与生成式AI如何变革未来餐饮科技报告(中译版)(18页).pdf

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1、 2024 Cognizant 2024 Cognizant How Edge Computing,Artificial Intelligence,and Generative AI are changing the future of restaurant technology 2|2024 Cognizant Abstract Frequent challenges faced by the restaurant industry can be categorized under three broad level segments,including low customer reten

2、tion,inefficient operations and inventory management and high labor cost.Low customer retention:The restaurant industry is highly competitive and fragmented,with customers having a wide range of choices and preferences.The percentage of customers who are loyal to a specific restaurant brand is decli

3、ning,whereas those who switch brands more than once a month is on the rise.To retain and attract customers,restaurants need to offer personalized and engaging experiences,such as customized menus,recommendations,rewards,and feedback.Inefficient operations and inventory management:The restaurant indu

4、stry faces various operational challenges,such as optimizing food quality and safety,reducing food waste and spoilage,managing supply chain and inventory,and complying with health and safety regulations.According to a report,the average food wastage in restaurants is 11%of food purchases,which amoun

5、ts to significant losses annually.To improve operational efficiency and profitability,restaurants need to leverage real-time data and analytics,automate processes,and optimize resources.High labor cost and turnover rates:The restaurant industry is one of the most labor-intensive sectors.According to

6、 a survey,98%of operators say higher labor costs are an issue for their restaurant.Moreover,the industry suffers from a high turnover rate which impacts the quality and consistency of service and increases training and hiring costs.This paper discusses how Edge Computing,AI,and Generative AI can hel

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本文主要探讨了边缘计算、人工智能和生成式人工智能如何改变餐饮业技术。文章指出,餐饮业面临的主要挑战包括客户留存率低、运营效率和库存管理低效以及劳动力成本高。边缘计算通过将计算能力更接近数据源,减少延迟并加快决策。餐厅使用边缘计算驱动的店内云技术,可以加快数据处理,提高系统可靠性。生成式人工智能可以生成新的内容,如图像、文本、音乐或视频,基于现有数据。文章还讨论了在边缘设备上部署大型语言模型(LLM)的技术挑战,包括模型量化。总体而言,边缘计算、人工智能和生成式人工智能的整合,有望通过降低成本和改进流程,提高餐饮业的盈利能力。
边缘计算如何帮助餐饮业提高客户留存率? 生成式AI如何优化餐饮业的库存管理? 边缘计算与生成式AI如何降低餐饮业的劳动力成本?
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