Three Cool Applications of GANs in eCommerce
Learn how AI-empowered Generative Adversarial Networks can help you grow your eCommerce business.
What is GAN (Generative Adversarial Network)?
GANs have been around for a while. Have you heard of FACE APP or PRIZMA? They are impressive examples of what GANs can do. In simple words, GANs can create something from nothing as they generate data from scratch.
GANs generate images, music, voice, text, and videos. For example, in the image below, GAN generated a zebra from a horse.
GANs use two neural networks, setting them against one another (that’s why we call them “adversarial”). Opposing networks create new, synthetic data that resembles real data.
One neural network generates data instances (generator). Then another (discriminator) tests them for authenticity. It is the discriminator that determines whether the data it reviews is from the actual training dataset. The discriminator rates the quality of the results on a scale of 0 to 1. Low scores make the generator correct the data and resubmit it to the discriminator. The cycle repeats until the GAN creates data with the same statistics as the training set.
For example, GAN can be trained on images to generate new ones that have realistic characteristics and look authentic to observers. Here GANs generate images of people who do not exist.
Three Cool Applications of GANs in eCommerce:
1. Creation of fashion models with custom outfits.
GANs can produce high-resolution images and customize outfits and poses depending on a fashion model. They can reproduce the same fashion model in a variety of body types and outfits. GANs can create models that fit into the brand’s image and resembles the target audience. With GANs, fashion brands can even create their own “artificial” social media influencers.
2. Enhanced product descriptions and personalized customer interactions.
GANs can generate marketing texts and reword the phasing of a product description to include user-defined keywords.
GANs-produced texts are becoming more difficult to distinguish from a human-written content. GANs can convert text to images and generate examples of products that match textual descriptions.
It can offer the user a visual guide where the user can refine the text query until he or she finds the right product. Machine interactions (e.g. Chatbots) appear more natural as GANs learn how to respond in a more natural form.
3. Creation of personalized products.
Ever listened to your favorite song and had images in your head? Imagine having customized products, for example, headsets or phone covers that remind you of your favorite music?
GANs can convert audio into images. Check out these examples of what they produce. If GANs can create art from the sound, we can apply the generated technique to the product to make it unique.
Consumers always look for custom products, and the demand for them will only increase. So we expect GANs to become extensively adopted in e-Commerce.
GANs will take online shopping experience in e-Commerce to a new level and help retailers engage and keep their customers.
Besides what we have mentioned, GANs can also generate 3D objects and cartoon characters. GANs have capabilities for video prediction, production and alteration of video content, image-to-image translation, and much more.