ChatGPT Vision: Bridging Textual and Visual Realms (With Implications For Assessment)

Instead of being limited to textual interactions, this extended model can analyze images, bridging the gap between textual and visual information.

What is ChatGPT Vision?

Expanding its capabilities, OpenAI is introducing ChatGPT Vision, a model designed to process both textual and visual inputs.

Unlike the traditional ChatGPT which operates solely on textual data, ChatGPT Vision integrates visual understanding. This allows it to interpret images, providing insights or answering questions related to visual content. While still rooted in the foundational principles of the GPT-4 architecture, this iteration represents an intersection of language and visual processing.

The emergence of ChatGPT Vision underscores the importance of multi-modal AI models now that LLM AI are multiplying like rabbits.

Watch this section in particular (6:57 - Math Homework) to understand possible implications for assessment at UNIC in your subject area.

Check out this video by Matthew Berman, with 22 examples of use-cases for ChatGPT Vision:

For your reference, these are the time-stamps:

0:00 - Intro 0:39 - Reasoning & Human Nature 2:18 - Human Cell Diagram 2:57 - Food & Recipes 3:38 - Circuit Diagram 4:12 - Mushrooms and Effects 4:54 - Interior Design 5:30 - Human Brain Complex Diagram 6:22 - Complex Parking Signs (Logic) 6:57 - Math Homework 7:40 - Architecture 8:37 - Research Paper (Education) 9:15 - ChatGPT Voice Dialogue 10:12 - Architecture & Building 11:10 - Crossword Puzzle (Reasoning) 11:32 - Image to Code 12:03 - Design to Code 12:43 - Image Recognition 14:03 - Image to Code 14:49 - Movie/Character Recognition 15:24 - Poker & Strategy 16:12 - Image Recognition 16:58 - Image to Code 17:26 - Chart Analysis 17:53 - Final Thoughts