Feb. 6, 2024, 5:47 a.m. | Anna Yoo Jeong Ha Josephine Passananti Ronik Bhaskar Shawn Shan Reid Southen Haitao Zheng Ben Y. Zhao

cs.LG updates on arXiv.org arxiv.org

The advent of generative AI images has completely disrupted the art world. Identifying AI generated images from human art is a challenging problem whose impact is growing over time. The failure to address this problem allows bad actors to defraud individuals paying a premium for human art, and companies whose stated policies forbid AI imagery. This is also critical for AI model trainers, who need to filter training data to avoid potential model collapse. There are several different approaches to …

actors ai generated ai-generated images ai images art companies cs.ai cs.cv cs.lg failure generated generative human images impact world

ML/AI Engineer / NLP Expert - Custom LLM Development (x/f/m)

@ HelloBetter | Remote

Doctoral Researcher (m/f/div) in Automated Processing of Bioimages

@ Leibniz Institute for Natural Product Research and Infection Biology (Leibniz-HKI) | Jena

Seeking Developers and Engineers for AI T-Shirt Generator Project

@ Chevon Hicks | Remote

Cloud Data Platform Engineer

@ First Central | Home Office (Remote)

Associate Director, Data Science

@ MSD | USA - New Jersey - Rahway

Data Scientist Sr.

@ MSD | CHL - Santiago - Santiago (Calle Mariano)