Gene Kogan is a New York based artist studying machine learning through sound and artworks. He dove into neural networks and the algorithms that allow them to act as artificial intelligence and their ability to create images. Through machine learning these networks can analyze images, handwriting, specific objects, and search for recurring themes and styles. These images often take on abstract and painterly forms naturally, but he also explores purposefully applying these algorithms to transform images and videos as a medium for creative expression. The ability for computers to almost autonomously create visuals that resemble painterly styles is quite stunning (whether it be abstract or combining the Starry Night and Mona Lisa. Kogan breaks down machine learning, such as the way neural networks operate, into simpler and easier to understand lectures for the mass audience. In addition to content he publishes online, he has taught classes at NYU, Bennington College, and SchoolOfMa. He has been a part of international open source projects and writes code for visual and sound performances.

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