Researchers have developed an AI “fashion designer” that can generate personalized apparel designs on the basis of preferences of a person. The system, designed by scientists in the U.S. at the University of California San Diego, planned to examine how well instruments from machine learning and AI (artificial intelligence) can assist the consumers as well as fashion industry.
While there are a lot of tools and algorithms to assist online sellers suggest designs to potential purchasers, team needed to look if it might be achievable to crunch other data including preference to make suggestions, and allow computers to generate customized designs of clothing. “We demonstrate that our model can be utilized generatively, that is, given a product segment and a user, we can make fresh pics (in this case clothing product) that are most dependable with the personal taste of the user,” claimed PhD student at UC San Diego, Wang-Cheng Kang, to the media in an interview.
“This symbolizes a first measure toward making systems that exceed suggesting present goods from a range of products, to recommending styles and assisting to design fresh goods,” claimed Kang. Researchers aimed on developing a system to generate better suggestions, mainly in the case of visual suggestions, where users can be influenced by how the item looks, as in the case of artworks or fashion apparel.
“This recommends a new kind of suggestion approach that can be employed for production, recommendation, and design,” claimed professor at UC San Diego, Julian McAuley, to the media in an interview. “These structures can result in richer kinds of suggestion, where content generation and content recommendation are more strongly connected,” claimed McAuley. “Building effectual adviser systems for segments such as fashion is tough owing to the semantic complexity of the features compromised and the huge level of subjectivity,” he claimed.