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Matthew Berman looks at fictional AI-generated images of public figures and tests image prompts in Grok 2. He characterizes the tool as uncensored and contrasts it with DALL·E, but the few examples do not establish either system's complete safety rules or current behavior. The images are synthetic, not evidence of real events.
- 1A 2024 image toolBerman introduces Grok 2's image generation and calls it uncensored. The brief demonstration is not a comprehensive safety test.
- 2Fictional public-figure imagesHe reviews generated images depicting public figures in invented situations; they are not real photographs of the events portrayed.
- 3Two example promptsBerman tries prompts involving Elon Musk and Mark Zuckerberg and contrasts the results with his understanding of DALL·E.
Conclusiones
- Berman examines fictional generated images of public figures and submits two further prompts.
- He describes Grok's 2024 behavior as less restrictive than DALL·E in these examples.
- A small set of prompts does not establish that an image system has no safeguards.
- Generated images of real people should not be treated as records of actual events.
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Generated examples
Berman introduces Grok 2 and reviews fictional images of public figures.
Matthew Berman introduces Grok 2's image generation and looks at fictional images involving public figures, including Taylor Swift, Donald Trump and Kamala Harris. These are synthetic depictions, not evidence that the portrayed events occurred.
Trying prompts
He submits two prompts and compares the experience with DALL·E. The sample is too small to establish complete policy differences.
Berman then requests an invented image of Elon Musk and another based on Mark Zuckerberg's public style, and comments on the results. He contrasts the experience with DALL·E in ChatGPT. His description of Grok as completely uncensored is a judgment based on a small set of 2024 examples, not proof that no safeguards exist or a description of current policy.
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