What you could know
- Look AI makes use of selfies and person knowledge to create AI-curated, stylized vogue appears to be like.
- Customers can additional discover appears to be like, uncover merchandise, and make purchases from over 400 world manufacturers with a single faucet.
- Look AI is constructed on a three-layered AI structure, together with commerce intelligence, generative expertise, and transaction journeys fashions — aiming for hyper-realistic and customized outcomes.
Look is introducing a brand new AI-native procuring expertise, which makes use of a selfie to curate generative visuals, which might additional be set in your smartphone’s lock display, and it’s dubbed Look AI.
Think about looking for an outfit via standard e-commerce shops, which normally showcase a number of merchandise to browse or search. Look AI, however, places the person up entrance via their selfie and generates an AI-curated, stylized look.
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As seen within the shared pictures, a person must open up the Look AI app, embody their selfie, and provides crucial particulars like age, physique kind, gender, and hit generate. The app’s AI-native commerce engine then makes use of “diffusion fashions, personalization engines, and a reside commerce layer that maps every person’s distinctive AI look to actual, shoppable merchandise from curated manufacturers throughout the globe.”
With only a single faucet, customers who click on their picture or add a related picture will have the ability to discover appears to be like and merchandise per their preferences, and moreover, they may even have the ability to full the prompt product buy seamlessly. Look notes that these purchases might be remodeled 400 world manufacturers, together with Levi’s, Previous Navy, Tommy Hilfiger, and extra.
In a shared press launch, the corporate additional explains that the Look AI is constructed on a three-layered deep tech structure:
- Commerce Intelligence Mannequin; skilled on 20+ years of world commerce knowledge, studying from new developments, cultures, and client conduct.
- GenAI Expertise Mannequin, producing hyper-realistic visualizations primarily based on hundreds of parameters comparable to gender, physique kind, ethnicity, pores and skin tone, match, type, and season to simulate how a specific clothes will look on a person.
- Transaction Journey Mannequin, an agent that understands procuring intent earlier than customers do, pairing visualizations with the best-matched product from thousands and thousands of catalogues globally.
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Look, an India-based advert tech agency additionally backed by Google, signifies that the preliminary mannequin is tailor-made to the style trade, additional desires to discover classes like magnificence, equipment, and journey later this 12 months.
Look AI right here is claimed to be utilizing its most superior proprietary AI fashions. It’s believed to be incorporating fashions like Google Gemini, Imagen on Vertex AI, with an goal to ship a hyper-realistic and customized expertise to customers.
Additionally, the app is designed as an opt-in platform that features privateness and person management. And the AI-based stylized appears to be like might be saved or shared, and even set as wallpapers on lock screens, as aforementioned. It additionally desires to transcend app expertise because it desires to show telephones “into AI telephones, TVs into family commerce gadgets, and model shops into AI shopfronts.”
Look AI, though primarily based in India, has moved to the U.S. with trials that started last year. In line with the corporate, the app’s U.S. trials have seen a “sturdy client engagement for inspiration-led procuring.” The platform is claimed to have attracted greater than 1.5 million lively customers, and half of them returned weekly after making an attempt the expertise.
For Android phones and iOS gadgets, Look AI is launching as a standalone app globally via the Google Play Retailer and the Apple App Retailer, respectively. The corporate is promising the rollout with even deeper integrations for Android OEMs and telecom operators within the close to future.
