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AI vs a giraffe with no spots

May 27, 2024 - aiweirdness.com
The article discusses the limitations of AI image recognition algorithms, using the example of a spotless giraffe. Despite the giraffe's distinctive lack of spots, the AI models tested, including Multi-Modal In-Context Learning (MMICL) and Instruct-BLIP, failed to identify this unique feature. The author suggests that AI struggles with images it hasn't seen before, tends to overlook unusual aspects, and that the showcased successes of these models may not represent their overall performance.

The author also points out that giraffes have been a recurring issue in image recognition, with algorithms often incorrectly identifying them. The article concludes with a cautionary note about relying too heavily on AI for image recognition, as it can often miss obvious features. The author also mentions an unsuccessful attempt to get DALL-E2, another AI model, to generate an image of a giraffe with no spots.

Key takeaways:

  • AI image recognition algorithms struggle to identify unusual features in images, such as a giraffe without spots, likely due to a lack of similar images in their training data.
  • The algorithms tend to provide the most likely answer to a question, which may not necessarily be the most accurate, leading to a tendency to "sand away" the unusual.
  • While the models used in the experiment, MMICL and InstructBLIP, are modern and high-ranking, they still struggled with the task, suggesting this is a widespread issue in AI image recognition.
  • The article suggests that AI's limitations in image recognition should serve as a cautionary tale about placing too much faith in this technology.
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