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dc.contributor.authorMolina, Rachel X.
dc.date.accessioned2023-08-14T16:08:04Z
dc.date.available2023-08-14T16:08:04Z
dc.date.issued2023
dc.identifier.urihttp://hdl.handle.net/20.500.12648/11897
dc.description.abstractThe creative industry has been in turmoil since artificial intelligence (AI) has begun to generate its “own art.” But AI was not always this intelligent, there are many past models that are milestones in AI’s journey to image generation based on text prompts. Programs like OpenAI’s DALL-E* are able to generate an image based on a user’s text prompt, using a Contrastive Language-Image Pre-Training (CLIP) model, a diffusion model, and a prior model. Other programs created by smaller organizations or individuals, use some sort of image generator such as a generative adversarial network (GAN) plus CLIP to generate images based on text prompts. These AI programs have led to discussions regarding the legitimacy, or originality of these images, and the data images used to train the programs.
dc.subjectFirst Reader Irina R. Shablinsky
dc.subjectSenior Project
dc.subjectSemester Spring 2023
dc.titleBehind the Scenes of AI in Art
dc.typeSenior Project
refterms.dateFOA2023-08-14T16:08:04Z
dc.description.institutionPurchase College SUNY
dc.description.departmentMathematics & Computer Science
dc.description.degreelevelBachelor of Arts
dc.description.advisorShablinsky, Irina R.
dc.date.semesterSpring 2023
dc.accessibility.statementPurchase College - State University of New York (PC) is committed to ensuring that people with disabilities have an opportunity equal to that of their nondisabled peers to participate in the College’s programs, benefits, and services, including those delivered through electronic and information technology. If you encounter an access barrier with a specific item and have a remediation request, please contact lib.ir@purchase.edu.


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