Technology

Amazon extends generative AI-powered product listings to Europe

Amazon Extends Generative Ai Powered Product Listings To Europe

Solar Kat Latest Tech

Amazon is bringing its generative AI listing smarts to more sellers, revealing today that those in France, Germany, Italy, Spain and the U.K. can now access tools designed to improve product listings by generating product descriptions, titles and associated details.

Additionally, sellers can also “enrich” existing product listings by automatically adding missing information.

The launch comes nine months after Amazon first revealed plans to bring generative AI technology to sellers. The company hasn’t been overly forthcoming about which market the tech will be available in, but it has largely been limited to the U.S. so far. That said, the company did quietly launch the tools in the U.K. earlier this month, according to an Amazon forum post.

In its blog post on Thursday, the company said it rolled out this feature in the U.K. and some EU markets “a few weeks ago,” and more than 30,000 of its sellers are apparently using these AI-enabled listing tools.

Amazon pitches these new tools as a way to help sellers list goods more quickly. Sellers can head to their List Your Products page as usual, where they can enter some relevant keywords that describe their product and simply hit the Create button to formulate the basis of a new listing. The seller can also generate a listing by uploading a photo via the Product Image tab.

Amazon marketing image for generative AI-powered listings
Amazon marketing image for generative AI-powered listings
Image Credits: Amazon

Amazon will then magic up a product title, bullet point and description that the seller can edit if they want to. However, given the propensity for large language models (LLMs) to hallucinate, it wouldn’t be prudent to post a listing unchecked — Amazon acknowledges that point by recommending that the seller reviews the copy “thoroughly” to ensure everything is correct.

“Our generative AI tools are constantly learning and evolving,” the company said on its U.K. forum two weeks back. “We’re actively developing powerful new capabilities to make generated listings more effective, and make it even easier for you to list products.”

Earlier this year, Amazon launched a new tool that allows sellers to generate product listings by posting a URL to their existing website. It’s not clear when, or if, Amazon will be extending this functionality to Europe or other markets outside the U.S.

The data question

While Amazon is no stranger to AI and machine learning across its vast e-commerce empire, bringing any form of AI to European markets raises some potential issues around regulation. There’s GDPR on the data privacy side for starters, not to mention the Digital Services Act (DSA) on the algorithmic risk side, with Amazon’s online store designated as a Very Large Online Platform (VLOP) for the purposes of ensuring transparency in the application of AI.

For context, Meta last week was forced to pause plans to train its AI on European users’ public posts. Amazon itself has faced the wrath of EU regulators in the past over its misuse of merchant data, when it was alleged that Amazon tapped non-public data from third-party sellers to benefit its own competing business as a retailer. And just this month, U.K. retailers hit Amazon with a £1.1 billion lawsuit over similar accusations.

While Amazon’s latest foray into generative AI is a different proposition, its LLMs have to be trained on some sort of data — what data this is, precisely, isn’t clear. In its initial announcement last September, Amazon shared a quote from its VP of selection and catalog systems, Robert Tekiela, who referred to “diverse sources of information.”

With our new generative AI models, we can infer, improve, and enrich product knowledge at an unprecedented scale and with dramatic improvement in quality, performance, and efficiency. Our models learn to infer product information through the diverse sources of information, latent knowledge, and logical reasoning that they learn. For example, they can infer a table is round if specifications list a diameter or infer the collar style of a shirt from its image.

Robert Tekiela, VP of Amazon Selection and Catalog Systems

TechCrunch has reached out to Amazon for comment on these various issues, and will update when we hear back.

source

solarkat
the authorsolarkat

Leave a Reply