Amazon says it uses a large number of AI and ML algorithms from the point we search a product and until it reaches our doorstep.
“Machine learning is ubiquitous on Amazon today,” said Rajeev Rastogi, vice president, machine learning, Amazon India, in an interview with Gadgets 360. “In the retail industry, we make extensive use of l ‘machine learning to recommend products to customers, predict future demand for products, and improve the quality of a product catalog, both by categorizing products and eliminating duplicate products.
One of the most basic examples of the way Amazon uses machine learning (ML) is typing a query into its search bar. , Rastogi noted, examines the phonetic distance between the misspelled query and the correct query instead of looking at their text distance to provide accurate results whether or not you’ve typed something. For example, if you type “geezar” on Amazon to search for geyser options, the market will automatically correct the orthgr afia and it will show you relevant results. Amazon also uses ML models to translate content on its site into the Indian languages it now supports.
Of course, this kind of computer use is now common and it’s not something most of us think of when we consider the terms artificial intelligence (AI) or machine learning. Rastogi revealed that his team is currently working on a startup initiative that aims to bring a conversational shopping experience. It is aimed at new online shoppers who are more accustomed to communicating with offline retailers than placing an order through an e-commerce site. Conversational commerce, through chatbots, through smart assistants like Amazon’s Alexa, is one of those ideas that comes up every few years as technology improves, and Rastogi explains how it’s going to start with text. , in English, but expand into other languages. and by voice. “A machine can read a document and then answer any question about the document, it’s difficult. Today, AI cannot generate a review for a film, for example … Even summarize a whole of documents is a difficult problem. solved by artificial intelligence by all means, “said Rastogi.
Artificial intelligence has been used to analyze text and speech at different levels. But computer engineers and data scientists have not yet been able to find a relevant blend to use artificial intelligence and machine learning to generate accurate ratings such as movie or product reviews. In a research paper, published by researchers Gerit Wagner, Roman Lukyanenko and Guy Paré from the Department of Information Technology, HEC Montréal, on how artificial intelligence can be used in the literature review process , it is noted that “technically perfect tools (like researchers)” sometimes have difficulty evaluating information from sources that use ambiguous and confusing language and presentation.McKinsey Global Institute (MGI) Mickinsey Chui Partners, James Manika, and Mehdi Miremadi also stressed in an article that models that models have “difficulty bringing their experiences in a series of different circumstances” and require companies.And which products suit you? “, did he declare. Dealing with Bias and Errors One of the biggest challenges in using AI and ML today is limiting bias and errors.
Companies from Google and Facebook to Microsoft regularly deal with these errors. Even Amazon is not foolproof. Sekar of the University of Toronto Scarborough and the Rotman School of Management noted that Amazon’s AI implementations include many biases that the company is already aware of and apparently working to address, but we don’t not know to what extent she achieved the desired results. “For example, maybe historically, users have clicked on a particular brand of headphones, so what happens is that in the future I will continue to amplify that brand exactly over and over again. It’s usually called a kind of popularity bias where I try to highlight products that are already popular, and basically I’m helping the rich get richer in the system, “he said. However, he disagreed and said
Amazon’s goal is to help human workers, not replace them entirely.Who helps ? Using AI and ML helps Amazon deliver what you need by understanding your buying behavior and buying history. However, this sometimes leads to impulse buying and just convinces you to buy something that you don’t actually need. Experts believe it would grow further with a more conversational shopping experience. “I think AI and machine learning can definitely increase the conversion of storefront buyers to repeat buyers,” Sekar said. “And that’s certainly a good way to think of Amazon as a persuasive seller. Consumers themselves can overcome this behavior by understanding how algorithms can influence their choices.” Even though we’re going to click on a product to buy it from in the end, we’re sort of guided along the buying funnel by the algorithm in different places