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World Creativity and Innovation Day is a time to celebrate the power of human imagination and innovation. Over the years, we have witnessed tremendous advancements in technology that have enabled us to accomplish incredible feats, and artificial intelligence (AI) is no exception. AI has emerged as a critical tool in today's digital age, bringing creativity and innovation together like never before.
On the dawn of Artificial Intelligence becoming mainstream in day to day life, big questions about its influence in the artworld loom large. From answering simple queries, to copywriting, to generating complete artworks, the possibilities of AI seem both inspiring and overwhelming. This week, we’re delving into the world of AI and providing an overview of the ground-breaking technologies integrating into the art world. We’ll help you through a crash course in understanding AI and some of the possibilities and issues that surround this new tool.

What is AI?

AI refers to the ability of machines or computer programs to perform tasks that typically require human intelligence. It involves the development of algorithms and computer programs that can analyze and learn from data, and make decisions or predictions based on that learning.

AI has been used to create art through a technique called generative art. In this approach, an artist provides the algorithm or the computer program with a set of rules and instructions that the program will use to create a piece of art. These rules can include things like color choices, shapes, and composition. The program then generates a piece based on all of these instructions, pulling data from information available.
One of the popular AI techniques used in generative art is called neural style transfer. Neural style transfer involves using a deep neural network to apply the style of one image to another image. This technique can be used to create new art pieces by combining the content of one image with the style of another.

Another technique used in AI art is called GANs (Generative Adversarial Networks). GANs are a type of neural network that can learn to generate images by training on a large dataset of images. GANs work by having two neural networks compete with each other, where one network generates fake images and the other network tries to distinguish between the real and fake images. Through this process, the generator network learns to create more realistic images over time. In short, the more images are generated, the more data the program has to learn from and refine its process.

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• #Influence
• #Art World
• #artificial intelligence
• #technique
• #algorithms
• #programs