The Basics of AI in Image Generation
AI in image generation uses advanced algorithms, particularly neural networks, to create visual content. The most common technology behind these systems is Generative Adversarial Networks (GANs), where two neural networks—a generator and a discriminator—work together. The generator creates images, while the discriminator evaluates them, improving the generator's output over time.
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GANs are particularly powerful because they learn from vast datasets of images, such as photographs, paintings, or digital art. The generator tries to mimic real images, and the discriminator’s job is to identify whether the image is real or generated. Over thousands of iterations, the generator becomes capable of producing highly realistic images.