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Generative Artificial Intelligence and E-Commerce

计算机科学 生成语法 人工智能 数据科学
作者
Nir Kshetri
出处
期刊:IEEE Computer [IEEE Computer Society]
卷期号:57 (2): 125-128 被引量:2
标识
DOI:10.1109/mc.2023.3340772
摘要

enerative artificial intelligence (GAI) is poised to bring about transformative changes in the e-commerce industry and market.E-commerce giants such as Alibaba, Amazon, and JD, and startups such as grocery delivery platform Instacart have deployed GAI applications to facilitate e-commerce activities.Noteworthy large-scale retailers have also rolled out similar solutions in the market.In June 2023, French grocery chain Carrefour announced its plan to deploy three solutions based on OpenAI's GPT-4 and ChatGPT: 1) an advice robot to help shopping on carrefour.fr,2) description sheets for Carrefour-brand products that provide detail of every product on its website, and 3) support for purchasing procedures.The chain's ChatGPT-based Hopla helps customers with their daily shopping.Customers can ask for help in choosing products based on budget, their food constraints or menu ideas. 1 Buyers and sellers can harness GAI to effectively address and manage a variety of challenges in their transactions.For instance, online shoppers are faced with various sources of uncertainty such as those related to vendor, product characteristics, and product fit. 2 GAI solutions can help reduce such uncertainties.To take an example, in June 2023, Google launched a GAI feature called virtual try-on tool for an immersive online shopping experience.It includes various models, sizes, skin tones, body shapes, ethnicities, and hair types.Users can fine-tune their product preferences and explore different options.The tool is powered by Google's internally developed diffusion-based model, aiming to enhance everyday activities like shopping.Initially available to U.S. shoppers with models from brands like Anthropologie, Everlane, H&M, and LOFT, it will expand to other countries soon.Virtual fitting tools can reduce returns by providing users with a clearer understanding of fit and color.

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