What does it do? A neural network for creating content removes routine duties from copywriters, editors, rewriters. It searches for errors, changes technical parameters (resolution, size), converts formats, for example, from sound to text.
What to pay attention to? Neural networks work with any content that is useful for business. However, this does not mean that the program will replace specialists in the field of copywriting or design.
The article explains:
Types of content created by neural networks
9 rules for working with a neural network to generate content
8 Neural Networks germany email list for Text Content
Neural networks for generating graphic content
Neural networks for working with video content
4 neural networks for working with sound
Pitfalls of Using Neural Network-Generated Content
Frequently asked questions about neural networks for content
5 Scenarios for Using Neural Networks to Increase Website Profits by 40%
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Types of content created by neural networks
There are two options for how artificial intelligence can create a media product:
The content is developed by a neural network from scratch. The result is a special and complete project.
The programs are assigned some practical tasks: changing part of the picture, removing noise from audio, rewriting text.
So far, these processes cannot be called creativity, since both options use algorithms. And yet, the capabilities of neural networks are surprising.
Next, we'll learn about what artificial intelligence is capable of in the content creation process.
Text material
In this area, the first successful neural network for content was GPT-3. It is a computer language model capable of forming coherent paragraphs and even chapters. In some cases, its style is difficult to distinguish from human speech.
The neural network contains 46 TB of Internet texts. Based on them, the model assumes which formulations and in which contexts are used most often. To write a text, it is enough to specify a few introductory words. What is especially surprising is that the system can adhere to a specific style: if the introductory words are slang, then the entire text will have features of colloquial vocabulary.
The GPT-3 neural network turned out to be very successful, so it was taken as a basis for a number of other programs (for creating images and videos). The famous DALL-E system also works with GPT-3 mechanisms.
ChatGPT
Video content
After images, scientists taught artificial intelligence to generate unique videos based on verbal descriptions. A Chinese research group was the first in this direction with its program CogVideo. It works almost the same way as Dall-E or Imagen: first it creates a series of related pictures, and then it builds them into a logical chain to form the dynamics of the plot.
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