BERLIN, GERMANY – MAY 19: Symbolic photo on the topic of online shopping. The symbol of shopping … [+]
AI divides. In today’s modern workplace, most believe that the impact of artificial intelligence (AI) and its new generative source of wonder will transform the way we work in the months and years to come. While some are still reluctant to exploit its potential benefits (journalists and people in high-level decision-making positions may be among the most skeptical), data science theorists assure us that even opponents of AI will find soon an attractive subliminal element in AI functionalities. appear in applications without announcing itself as an automatic robot or a latest generation intelligent assistant.
Among the groups that appear poised to adopt AI relatively readily are web developers, particularly those who handle a large number of image-centric tasks as they work to classify, categorize, manipulate, and present pictorial assets for our online applications to illustrate our lives. .
Why are web images a chore?
To validate this suggestion, we need to know why working with web images can be such a chore, right? The fact is that advanced image editing and asset optimization for human accessibility and search engine optimization (SEO) is one of the main reasons why web development teams experience bottlenecks bottleneck in terms of resources.
In a recent independent investigation conducted in association with an image and video technology platform company Cloudy, more than half of web developers said they considered AI tools to be “very” or “extremely” reliable, citing improved efficiency and productivity as a major benefit. This workplace analytics study suggests that two-thirds of web developers are happy to use generative AI tools to streamline the development process and drive factors like workflow automation.
Enterprise digital asset management (DAM) specialist Cloudinary clearly thinks this is good news. The company’s generative AI capabilities provide a way to edit images at scale, enabling technical and non-technical users to showcase their most valuable assets online and prepare them for commercialization. Championing the idea of AI as a driver of employee autonomy and productivity, the company’s new Generative AI Upscale for Faces feature offers an example of the impact of generative AI.
Put a face on it
Images with faces have been found to attract attention and build confidence at higher rates; they are therefore among the most important elements of any image in which they appear. Likewise, user-generated content (i.e. photos that customers of products and services may have submitted to online shopping and shopping websites) is particularly useful in increasing customer conversions, but ensuring the necessary quality of human subjects when using these assets can be a challenging and time-consuming proposition.
“Generative AI continues to provide a quick and easy solution for developers and non-technical users to edit, optimize and deliver the best possible asset to any viewer, regardless of their viewing context,” said Nadav Soferman , co-founder and product director. at Cloudinary. “Building on our heritage of AI innovation, we are proud to bring these cutting-edge tools to our customers so they can not only unleash the full power of their images and videos, but also repurpose their time to more strategic and impactful work. .”
Cloudinary’s Generative AI Upscale for Faces uses advanced facial recognition technology to detect human faces. It is able to automatically optimize the image to ensure that faces remain visible and sharp, even when the original photo needs to be cropped and/or enlarged. This feature reduces risks associated with user-generated content (UGC) or other assets when the brand has no control over the original quality, thereby improving usability.
Repeatable and automated workflows
Cloudinary is also making more generative AI capabilities available to marketers and creatives with the upcoming update to the Studio feature of its enterprise digital asset management platform, Cloudinary Assets. Studio users, who already have code-free access to generative fill, replace, and recolor features, will be able to use generative restoration to automatically enhance and optimize many low-quality images at once. Studio users also have the ability to create automated, repeatable workflows to apply these transformations and deploy the upgraded assets across different channels.
This may seem like a relatively narrow application of generative AI and not everyone knows someone who is a web developer specializing in image management and manipulation. But everyone has used the Internet, everyone has visited online shopping pages, and every one of us has bashed our eyes at images of products and services wondering if the quality of the stitching is good enough and if this purple color is going to look like some kind of sickly purple flea in real life.