How Amazon’s AI is Paving the Way to a Greener Tomorrow?
Introduction
Amazon recognizes the urgency of the climate crisis and the need to create a more sustainable business by acting swiftly, innovating continuously, investing wisely, and maintaining a flexible organizational structure. We can accomplish our climate goals more quickly, on a larger scale, and with more urgency if we use AI and ML. A lot of people are talking about “AI and Sustainability” in general, but we felt it would be useful to focus on a few new use cases, which are explained below.
Rufus, a new conversational shopping experience powered by generative AI, has been announced by Amazon. For decades, Amazon has been at the forefront of AI and ML innovation, using these technologies to do anything from power fulfillment operations more efficiently to reduce packaging and food waste. In addition to providing AI infrastructure and products to clients through Amazon Web Services (AWS), our goal is to make AI accessible to everybody. This will allow our customers and other businesses to make more sustainable purchases, and life in general, more quickly.
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How Amazon’s AI is Paving the Way to a Greener Tomorrow?
- Reducing packaging use
An artificial intelligence algorithm called the Packaging Decision Engine helps Amazon figure out the best way to package and ship all of the millions of products they sell. After training the model with consumer feedback on the efficacy of various packing solutions, data scientists have taught it to recognize a wide range of product features, such as shape and durability. Launched in 2019, the model is continuously learning and has contributed to a decrease in the company’s packaging material usage. Since 2015, Amazon has reduced its global packaging by more than two million tons thanks to these and other improvements.
- Reducing returns by helping customers find the perfect fit
Shopping becomes more environmentally friendly when returns are reduced. Customers can browse for fashion with increased confidence in Amazon’s store thanks to many AI-powered advancements, and the company has seen a decrease in returns related to fit. Improved size charts, tailored comments from other customers who wear the same size, and AI and ML-powered personalized size suggestions are all part of the package. Brands may more correctly describe their products for customers and reduce fit-related returns with the help of Amazon’s Fit Insights Tool, which helps brands and selling partners discover customer fit issues and incorporate input into future designs and manufacturing.
- Measuring the carbon footprint for products
- Using AWS chips to power AI more efficiently
By investing in AWS chips and other energy-efficient cloud infrastructure upgrades, Amazon is also helping to make AI a more sustainable technology. Reduce the speed and cost of training generative AI models with AWS Trainium, a high-performance machine learning processor. Some models can have their training time reduced from months to hours. As a result, there is a possibility of saving up to 50% in costs and up to 29% in energy consumption when compared to similar instances, all while reducing the power and money needed to develop new models.
- Identifying damaged items to prevent waste
In an effort to reduce the amount of damaged items sent to and returned by consumers, an increasing number of fulfillment centers are utilizing AI-powered technologies to detect damaged goods. After training on millions of photographs of both intact and damaged objects, the AI can now identify damaged goods three times more accurately than humans. When an Amazon employee notices that a product is defective and cannot be sent straight to a consumer, the item is taken back for evaluation and is either resold at a discount, donated, or put to another good use.
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