By skyforbes Since you are interested in hyperdimensional spaces and fractals (based on your art interests), this explanation might actually click for you better than for most people.
Here is the "translation" of how a picture becomes a list of numbers (a vector).
- The Starting Point: The "Spreadsheet"
To a computer, that photo of the ramen pot isn't a picture. It is a giant spreadsheet.
* Imagine a grid that is 1000 pixels wide by 1000 pixels tall.
* Every single square contains three numbers: Red, Green, Blue.
* The yellow pot isn't "yellow"; it is a cluster of pixels that read something like R:255, G:215, B:0 (Gold).
- The Compression: The "Flavor Profile"
This is the magic part. The AI cannot "think" about 1,000,000 individual pixels—that's too much noise. It needs to simplify.
Imagine you are tasting a complex soup. You don't list every single molecule of water and salt. You create a summary:
* Salty: 8/10
* Spicy: 4/10
* Hot: 9/10
A vector is exactly that. It is a list of scores that describe the essence of the image, ignoring the useless details.
- Creating the Vector (The "Filters")
How does it get those scores?
The model slides thousands of little transparent "stencils" over the image.
* Layer 1 (The Toddler Brain): One stencil looks for vertical lines. Another looks for curves. Another looks for the color yellow.
* Result: "Okay, lots of yellow curves here."
* Layer 2 (The Child Brain): It combines those. "Yellow" + "Curve" + "Shiny texture."
* Result: "This looks like a metallic object."
* Layer 3 (The Adult Brain): It creates the final Vector.
- The Final Vector: Coordinates in Hyper-Space
This is where your interest in multidimensional geometry comes in.
The AI takes those "flavor notes" and turns them into a single string of numbers. Let's imagine a tiny vector for that Ramen Pot:
[0.92, 0.04, 0.88, 0.12]
To the AI, these numbers might represent:
* 0.92 = "Food Related" (Very high)
* 0.04 = "Outdoor Scenery" (Very low)
* 0.88 = "Metallic/Shiny" (High)
* 0.12 = "Furry/Animal" (Low)
Here is the "Mind-Bending" part:
The AI doesn't just have 4 numbers. It usually has thousands (e.g., 1,024 or 4,096 dimensions).
It takes that image of the pot and plots it as a single point in a 4,000-dimensional space.
* In that massive geometric space, the "point" for Ramen Pot is located physically close to the "point" for Chopsticks and Hungry.
* It is far away from the "point" for Bicycles or Clouds.
So, to answer "How does it convey it to the verbal model?"
It is purely geometry.
* Vision Model: "I have processed this image. I am placing a pin at coordinate [34, 99, 102] in the hyper-dimensional universe."
* Language Model: "Okay, I am looking at my map of words. The word 'Ramen' and the word 'Pot' are located at coordinate [35, 98, 101]. That is extremely close to your pin. So, I will say this is a Ramen Pot."
Does that help visualize it? It’s basically mapping "meaning" as a physical location in a giant, invisible universe!