Neural networks are rapidly transforming many creative fields, and the photostock industry is no exception. Will artificial intelligence finally supplant traditional photostocks, leaving photographers unemployed, or is true creativity immortal?

Will neural networks replace photostocks

Is the use of neural networks a trend or a necessity?

Today, we see artificial intelligence generating images that are virtually indistinguishable from the work of a professional photographer. On the one hand, this frees up huge resources for the development of creativity, but on the other hand, it creates many problems, including the spread of fakes and low-quality content.

With the development of AI technologies, the use of graphical neural networks has become not only a trend but also a necessity for many design professionals.

This is due to the fact that neural networks provide new opportunities for creating and processing visual content, significantly speeding up and simplifying work processes.

Photographer vs. artificial intelligence

We have all heard many times about the rapid development of neural networks and how they are being heavily implemented in various industries. Artificial intelligence has not passed by photography either. Already contests began to send works made by non-photographers, and their organizers had to urgently rewrite the contest conditions, prohibiting the use of AI.

And now Adobe Photoshop with AI has been released, which promises to generate any image by text description. You formulate what you need, write it down, and the neural network produces a ready-made image. You don’t need a camera, equipment… You don’t even need the subject itself!

The emergence of such capabilities immediately raised concerns—will AI not supplant the long and laborious work of photographers, videographers, and retouchers? Will photographing, for example, dishes for menus remain a job for humans, or will there soon be no need for them? Is it still possible to find human-made royalty free vectors by Depositphotos, for example?

The use of AI has gone so far that now people are talking about the emergence of a new profession—”AI artist,” and they, in turn, are even giving interviews. Their work is different from the work of an ordinary artist and, in fact, is not particularly difficult: write a prompt, and then process the result in Photoshop or outline it so that the result looks less like the work of AI.

Do you find any contradiction in this? It seems like they are proudly promoting technologies, but at the same time they are trying to hide them. And then suddenly it turns out that people do not like open admission of content generation.

The illusion is destroyed not in a vacuum but in context: almost all the works of AI artists look, if not almost identical, then terribly similar to each other. Like NFT with monkeys, fortunately long forgotten.

Advantages of neural networks over photo stocks

At first glance, artificial intelligence and the graphic content it generates have a number of advantages over traditional photo stocks.

  • Speed and efficiency. Generating images with the help of neural networks is much faster than endlessly searching for a suitable image on a photo stock among a mass of similar photos. AI technologies help automate many routine processes, freeing up time for more creative work.
  • Individuality. Neural networks create unique images that precisely match the needs of the customer, as if a personal photographer created the photo according to your script. The capabilities of neural networks allow designers to experiment with new ideas that are difficult or expensive to realize with real photography.
  • Cost-effectiveness. Using paid graphic neural networks can be many times cheaper than buying images from photostocks, especially if a large amount of content is required.
  • Accessibility for beginners. There are various tools and platforms based on neural networks that are accessible even to novice designers. At the same time, it is important to be able to use not the neural network itself but the basic principles of graphic design and artistic skills, which can be mastered at special courses.

However, such synthetic creativity has a number of serious disadvantages.

Disadvantages of neural networks

  • Quality. Often, the quality of images created by neural networks may not meet the high standards required for professional content. In some cases, people have more or less than five fingers on their hand; in others, the position of picture elements relative to each other is unnatural.
  • Ethical issues. The neural network is being trained, but it is a rather long and multi-step process. Along the way, there may be many mishaps and unpleasant situations related to the generation of images that offend certain ethnic, religious, and other groups of people. At the same time, such offensive content may not be immediately recognized by the author, leading to serious legal consequences after its publication.
  • Authorship. The use of AI technologies raises many issues regarding copyright and originality of the created content.
  • Dependence on technology. Professionals can become overly dependent on neural network-based tools, which can limit their creativity, whereas AI itself needs to be constantly fed by the real-world creativity it learns from.

Examples of neural networks being used by professionals

Neural networks are actively used in various areas of design.

  • Advertising. Many advertising agencies use AI to create conceptual images and visual effects; in many cities, you may have seen such a banner.
  • Fashion. Fashion designers are using AI to create new collections and visualize ideas.
  • Multimedia. In film and animation, neural networks help create realistic special effects and characters.
  • Bloggers. Use artificial intelligence to create images for articles, blogs, video content, stories, etc.
  • Web developers. Neural networks generate icons, background images, and other elements of websites.

Neural networks will not replace humans

It is important to realize that neural networks are unlikely to replace humans completely. Creativity, creativity, sense of taste—all of this is still left to humans. To remain competitive and effectively use modern technologies, it is important to master traditional graphic design tools.

Design was, is, and will be, but AI can and should be utilized, confirming the basic thesis that neural networks do have a significant impact on the photostock industry, expanding creative opportunities and simplifying workflows.

Traditional design methods remain important and in demand. Human beings are the main specialists, and it is they who have the key role in creating creative content. Neural networks should be considered as an additional tool that helps professional designers unlock their potential and realize the most daring ideas.

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