Visual Generative AI Ecosystem Challenges with Richard Zhang - #656
Published:Nov 20, 2023 17:27
•1 min read
•Practical AI
Analysis
This article from Practical AI discusses the challenges of visual generative AI from an ecosystem perspective, featuring Richard Zhang from Adobe Research. The conversation covers perceptual metrics like LPIPS, which improve alignment between human perception and computer vision, and their use in models like Stable Diffusion. It also touches on the development of detection tools for fake visual content and the importance of generalization. Finally, the article explores data attribution and concept ablation, aiming to help artists manage their contributions to generative AI training datasets. The focus is on the practical implications of research in this rapidly evolving field.
Key Takeaways
- •The article highlights the importance of perceptual metrics like LPIPS in aligning human perception with computer vision in generative AI.
- •It discusses the need for robust detection tools to identify and address fake visual content generated by AI models.
- •The article emphasizes the ongoing research into data attribution and concept ablation to empower artists and manage their contributions to AI training data.
Reference
“We explore the research challenges that arise when regarding visual generative AI from an ecosystem perspective, considering the disparate needs of creators, consumers, and contributors.”