Amazon has officially launched this Artificial intelligence (AI) tool. generative for sellers who Create text for product listings, the company has reported. Specifically the new tool simplifies the way marketplace sellers create product descriptionsTitle and Listing Details «more complete and captivating«. «These new features make it faster and easier for sellers to offer new products and enrich existing offerings, so customers can make their purchasing decisions with greater confidence.“, emphasized the company.
Previously, creating product titles, bullet points, and descriptions for sellers required hard work. This is why Amazon makes these available to sellers new generative AI capabilities to simplify this processThis reduces the need to enter a lot of product-specific data into a single step. «The new features leverage large language models (LLMs), a type of machine learning model that is specifically trained on large amounts of data and can recognize, summarize, translate, predict and generate text and other content to create more complete product descriptions“explained the company.
With the new tool Sellers simply need to provide a short product description and Amazon will generate high-quality content for your review. Sellers have the option to expand it or submit the automatically generated content directly to the Amazon catalog.
These new features will help sellers create high-quality listings with less effort and present customers with more comprehensive and engaging product information that improves their shopping experience.
Traditional, Amazon has used machine learning and deep learning to automatically extract and enrich product information. «Our new generative AI models allow us to derive, improve and enrich product knowledge at an unprecedented scale, and with dramatic improvements in quality, performance and efficiency. Our models learn to infer product information based on the various sources of information, latent knowledge, and reasoning they learn. For example, they may infer that a table is round if a diameter is specified in the specifications, or infer the collar shape of a shirt from the image.“, Has underlined Robert Tekiela, Vice President of Amazon Selection and Catalog Systems.
«A more complete product description not only saves sellers time, but also helps improve the shopping experience. Customers receive more comprehensive product information as new technologies allow sellers to provide more comprehensive information with less effort« added the manager.
Good reception from the sellers
Amazon announced this new generative AI functions In Accelerate 2023, Amazon’s premier annual seller conference. In recent months, the company says, many providers have been testing the latest AI innovations and are currently “Most of them directly use the listing content that the AI model creates for itS”.
Simplifying the creation of listings using AI is one of the things Amazon is doing to help sellers to improve and increase your salesbut Amazon explained: “This is just the tip of the iceberg of how we plan to use AI to improve the seller experience and help more sellers succeed.«.
AI to detect damaged items
The Andy Jassy-led company continues to take steps toward the future and doesn’t want to be left behind in the AI race among major tech companies. Recently, Amazon also announced that it is continuing to develop an AI-based system to detect damaged items during the packaging process, so that they are taken out of operation and do not reach the customer. Amazon plans to implement this system in 12 logistics centers in North America and Europe before the Christmas campaign.
The project started last year when a team of scientists from Amazon fulfillment technologies discovered that they could use a machine learning model with reference images to teach the system to compare the product it was looking at with an image showing what that product should look like. To achieve this, scientists use computer vision techniques to scan every item that passes through their warehouse on the outskirts of the German capital. A machine learning model then analyzes the scans to uncover hidden patterns and detect potential damage. If an error goes unnoticed, experts analyze it and teach the AI to recognize it.