Summary of Can Ai Be As Creative As Humans?, by Haonan Wang et al.
Can AI Be as Creative as Humans?
by Haonan Wang, James Zou, Michael Mozer, Anirudh Goyal, Alex Lamb, Linjun Zhang, Weijie J Su, Zhun Deng, Michael Qizhe Xie, Hannah Brown, Kenji Kawaguchi
First submitted to arxiv on: 3 Jan 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: Computation and Language (cs.CL)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The paper investigates the creative potential of advanced generative AI models, which can perform tasks previously thought to be exclusive to human creativity. The authors prove that AI can be as creative as humans under certain conditions, reducing the debate on AI’s creativity to its ability to fit a sufficient amount of data. They introduce a new concept called Relative Creativity and shift the focus from universally defining creativity to statistically quantifying AI’s creative abilities. The authors analyze the results, revealing that by fitting extensive conditional data without marginalizing out the generative conditions, AI can emerge as a hypothetical new creator with the same creative abilities as human creators it was trained on. This study provides an actionable training guideline for evaluating the creative abilities of generative AI models like Large Language Models (LLMs) and offers practical means for prompt-conditioned autoregressive models. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper is about how well AI can create things, just like humans do. Researchers want to know if AI can be as creative as people are. They came up with a new way to measure creativity, which they call Relative Creativity. Instead of trying to define what makes something creative, they focus on whether AI can match the skills of human creators. The results show that when AI is trained on lots of data without forgetting how it was generated, it can become as creative as humans! This study also gives tips on how to train AI models to be more creative and even provides ways to measure their creativity. |
Keywords
» Artificial intelligence » Autoregressive » Prompt
