“Machine learning is ubiquitous these days at Amazon,” said Rajeev Rastogi, Vice President of Machine Learning at Amazon India. I am using machine learning extensively to recommend products to customers, forecast future demand for products, and improve the quality of my product portfolio, both categorizing products and removing products. duplicate. ”
One of the most basic examples of how Amazon using machine learning (ML) is when you misspelled a query in its search bar. E-commerce sites, Rastogi notes, consider the phonetic distance between the typed misspelled query and the correct query instead of looking at their text spacing to provide accurate results – regardless of your misspelled or not.
For example, if you type “geezer” on Amazon to search for available injector options, the marketplace will automatically correct the typos and show you relevant results. Amazon is also using ML models to translate the content on its website into Indian language currently supported.
Amazon uses machine learning to provide accurate search results even if your query is misspelled
Of course, these computer usage patterns are now commonplace and not what 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 seed initiative aimed at delivering a conversational shopping experience. It is aimed at first-time online shoppers who are more familiar with communicating with offline store owners through e-commerce ordering.
Conversational commerce, through chatbots, through smart assistants like Amazon’s Alexa, is one of those ideas that will return every few years as technology improves, and Rastogi talks about how it will start with text, in English, but developed into other languages, and voice.
“For a machine to be able to read a document and then answer any questions about that document, it’s hard. Nowadays, AI cannot generate reviews for a movie, for example… Even summarizing a set of documents is a difficult problem. It is not solved by AI in any way,” emphasized Rastogi.
Rajeev Rastogi acknowledges challenges with AI
Image source: Amazon
WHO has been used to analyze text and speech at various levels. But computer engineers and data scientists have yet to find the right combination for using AI and machine learning to generate reviews as accurate as movie or product reviews. In a research paper, published by researchers Gerit Wagner, Roman Lukyanenko and Guy Paré of the Department of Information Technology, HEC Montréal, on how AI can be used in the document review process, it note that even “technically perfect tools (like researchers)” sometimes have difficulty appreciating information from sources using ambiguous language and presentation.
McKinsey Global Institute (MGI) also partnered with Michael Chui, James Manyika and Mehdi Miremadi shown in an article that says AI models have “difficulty bringing their experiences from one context to another” and asks companies to train models even when the use cases are very alike. This adds additional resource requirements.
Shreyas Sekar, Assistant Professor of Operations Management in the Department of Management, University of Toronto Scarborough and Rotman School of Management, says it’s effective for an AI-based bot to communicate with humans and get them results Suitability, especially in markets including India, is uncertain. . Sekar finished extensive research about how e-commerce platforms are using machine learning at both the consumer and warehouse ends to enhance their operations.
“When you ask these chatbots, simple questions like no, will it rain tomorrow? Or can you play me the song from this movie? They do a wonderful job. But when you start getting more and more complicated questions, like this, can you help me find a good pair of shoes for my trip? I think it’s very difficult for chatbots or even Alexa to unambiguously categorize this question into what is your intention? What kind of person are you, and how are you different from others? And which products are right for you? ” he say.
Dealing with biases and flaws
One of the biggest challenges of using AI and ML today is limiting errors and biases. Companies from Google and Facebook arrive Microsoft are dealing with these mistakes on a regular basis. Amazon is also not stupid in which Previous.
Sekar of the University of Toronto Scarborough and the Rotman School of Management note that Amazon’s AI implementation includes a lot of biases that the company is aware of and appears to be working to address, but isn’t clear how it has achieved. how successful the desired outcome is.
“For example, maybe historically, a user clicked on a particular brand of headphones, then what happens is in the future I keep amplifying that exact brand over and over again. So this is often called some kind of popularity bias where I try to highlight products that are already popular and I’m basically helping the rich get richer in the system,” he said. mention.
However, Rastogi strongly disagrees and says that Amazon’s goal is to support workers, not replace them entirely.
Who does this help?
Using AI and ML helps Amazon deliver what you need by understanding your buying behavior and purchase history. This, however, sometimes lead to impulsive purchases and simply convince you to buy something you didn’t really ask for. Experts believe it will evolve further with a more conversational shopping experience.
“I think AI and ML can definitely increase the idea of converting window shoppers into regular shoppers,” says Sekar. “And this is definitely what I think is a good way to think of Amazon as a very convincing salesperson.”
Amazon uses AI and ML algorithms to convince customers to buy new products
Consumers can overcome this behavior on their own by understanding how algorithms can influence their choices.
“Even though we are the ones who click on the product to buy in the end, we are still guided along the shopping funnel by the algorithm in different places whether it is a recommendation or a review,” says Sekar. .
Ankur Bisen, Senior Partner and Head of Consumer, Food and Retail at management consulting firm Technopak, explains the nature of how Amazon uses its algorithms to entice consumers to buy much more exactly what advertising, marketing, and even retail store discounts did.
“Amazon is doing it with a lot of precision because it has been identified,” he said. “Conversational AI is not only close to the domain of Amazon monopoly. Yes, they’re great because of Alexa. But you will see conversational AI emerge in different forms powered by other technology platforms.”
