How AI and ML Are Powering Visual Experiences
Engaging with customers in today’s digital world is impossible without rich visuals, which are no longer part of the story but the story itself. Brands that not only survive but also thrive are those dedicated to delivering visual experiences across the customer journey’s touchpoints. However, managing the sheer volume of the rich media required to accomplish that is humanly impossible.
Creating and managing media-rich digital experiences at scale goes beyond the scope of human capabilities, requiring a level of detail and application of best practices that can only be achieved through automation. Plus, artificial intelligence (AI) and machine learning (ML) capabilities make it a breeze to communicate through visual media, such as by spotlighting context and key objects.
Instead of tackling mundane, repetitive chores, customer-experience teams should focus on innovative projects that require initiative, brain power, and interpersonal skills. Hence the importance of content-aware AI and ML, which can automate content workflows.
Since its inception in 2012, Cloudinary has been on a continual path of innovation aimed at creating, managing, and delivering engaging media at scale. In particular, we’ve been embedding AI and ML into features that automate intricate processes for managing the media required for brands to compete in the modern, visual-first experience economy.
Cloudinary Media Intelligence is the intelligence framework that powers the Cloudinary Media Experience Platform, on which our products are built. We have trained that framework on the largest set of media data in the industry, affording it a deep understanding of rich media and an ability to process imagery and video accurately and efficiently. Smart capabilities powered by Cloudinary Media Intelligence permeate all our products across the media’s lifecycle.
Here are the key features offered by Cloudinary Media Intelligence, all of which are significant time-savers that produce impressive results:
- Automatic content-aware cropping of images through AI
- Content-aware tagging of images
- Image background removal by content-aware AI
- Automatic selection of image formats for delivery
- Automatic creation of responsive images on demand
- Automatic transcription of video
- Content-aware compression or cropping of video
Subsequently, brands have reduced or eliminated menial tasks, efficiently processing visuals at scale while strategizing and building ambitious omnichannel visual experiences. The examples below demonstrate three top brands reaped benefits from intelligent automation.
- Expeditious shoot-to-web. When creating photography for a product line, a global sporting-apparel brand automated the workflows for editing and cropping background elements, auto-tagging for searchability, and delivering final variations in a fraction of the time needed before.
- Automated transformation and optimization of images and video. A dating app automates the uploading of customers’ images and videos from multiple device types while resizing and cropping images on the fly, as well as optimizing the media format and quality to improve the user experience.
- Automated text overlay. A clothing–design company automates image transformation for its customers, for example, by transforming an image of a plain shirt into one with the shopper’s preferences so as to show what the shirt would look like after those personalizations are factored in.
We built Cloudinary Media Intelligence after determining that an ever-growing need exists for incorporating AI and ML throughout the media lifecycle as a crucial step for generating engaging user experiences. In the times ahead, in addition to building applications and functionalities, we’ll focus on understanding objects through context and other environmental parameters.
Here are three exciting and innovative AI-related projects currently underway at Cloudinary:
- Fashion AI — This feature trains Cloudinary Media Intelligence on the fashion domain so that brands can better fulfill their media needs.
- Custom AI — These are customizable AI models that help brands meet their unique requirements for media-related tasks or acquire subject-matter expertise that pertains to their products.
- Shop-the-look AI — This is a helpful and fun capability whereby shoppers would, for instance, provide a picture of a shirt in quest of similar designs among the available merchandise offerings.
From Day One at Cloudinary, the Cloudinary Media Intelligence framework has been helping our customers achieve what’s deemed impossible. Do have a look at the details of the framework. Given that innovation is in our DNA, we will continue to look for ways in which to scale visual experiences with our media-centric approach for intelligence and automation.
