{"id":61711,"date":"2023-02-08T16:04:55","date_gmt":"2023-02-08T16:04:55","guid":{"rendered":"https:\/\/villa-albertine.org\/professionals\/creating-ai\/"},"modified":"2024-01-27T20:45:03","modified_gmt":"2024-01-27T20:45:03","slug":"creating-ai","status":"publish","type":"app_professional","link":"https:\/\/villa-albertine.org\/va\/professionals\/creating-ai\/","title":{"rendered":"Creating with an AI"},"content":{"rendered":"

What is AI art? Is AI as creative as humans? Will AI replace artists in contemporary societies? Philosopher and researcher\u00a0Rapha\u00ebl Milli\u00e8re<\/a><\/strong>, Presidential Scholar in Society and Neuroscience at Columbia University,\u00a0defines the terms of the debate: \u201cAI art is generative, meaning that it is created using, at least in part, autonomous processes that do not centrally involve human input.\u201d\u00a0\u00a0<\/p>\n\n

Most algorithms used by AI artists are text-to-image generators such as\u00a0Stable Diffusion<\/a>,\u00a0DALL-E<\/a>, or\u00a0Midjourney<\/a>: they take text prompts as input and produce images as outputs. They belong to a class of algorithms called \u201cartificial neural networks\u201d (ANNs). An image generation ANN can learn from millions of images paired with their captions to generate images based on text prompts. The choice of the data used to train an ANN is, therefore, of prime importance, as it is reflected in the kind of outputs it will produce explains Milli\u00e8re: \u201cTraining an image generation ANN on early Italian Renaissance portraits might enable it to generate images that closely match the specific style of such portraits, but not any other style. Consequently, some AI artists like to train their own algorithms by curating a custom dataset on which to train them. This curatorial activity has much in common with museum curation.\u201d\u00a0\u00a0<\/p>\n

\n\t
\n\t\t