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How does a neural network work?
A neural network simulates the human nervous system, which is characterized by its ability to learn from previous experience. Thus, the system makes fewer and fewer mistakes each time.
Like our nervous system, a neural network consists of individual computational elements – neurons, located on several layers. Data arriving at the input of a neural network are processed sequentially at each layer of the network. Each neuron has certain parameters that can be changed depending on the results obtained – this is the training of the network.
Suppose that the task of the neural network is to distinguish cats from dogs. To tune the neural network, a large array of signed images of cats and dogs is fed. The neural network analyzes the features (including lines, shapes, size and color) in these pictures and builds a recognition model that minimizes the percentage of errors relative to the reference results.
What neural networks are used for?
Neural networks are used to animate characters in video games, films, and virtual reality experiences. Motion capture technology combined with deep learning algorithms enables realistic and expressive character animations that respond to user input and environmental stimuli. AI-driven animation tools streamline the animation process and enhance the quality and believability of character performances.
While controversial, the technology of deepnude apps, which uses neural networks to manipulate videos and images to replace one person’s likeness with another, has been used for entertainment purposes. Deepfake videos and images, often created for comedic or satirical purposes, generate buzz and engage audiences with their uncanny and sometimes surreal depictions of celebrities and public figures.
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