The present research utilizes three popular multimodal AI systems (Gemini, Cloud AI, ChatGPT) to evaluate their ability to interpret visual language by analyzing responses to three different images. In addition to evaluating the systems' ability to produce accurate and detailed descriptions of each image, this research evaluated their ability to contextualize each description within an appropriate framework of understanding, as well as assess their response times. Results indicate that ChatGPT provided the most accurate and descriptive descriptions of the images analyzed in this study, particularly those which depicted emotionally and/or socially nuanced scenes; that Gemini performed reasonably well in terms of conceptual interpretation, though was inconsistent in its provision of specific details regarding the image(s); and that while Cloud AI responded more quickly than either ChatGPT or Gemini, it failed to provide as much detail or relevance to the situation presented in the images. These findings emphasize the need to develop multimodal AI systems that balance speed, emotional intelligence, and semantic accuracy to be used in the real world when reasoning with images.

Artificial Intelligence, Gemini, Natural Language processing

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