Using a pasta machine to send a photo through creates pixelated, simplified versions of the image. This is a great way to illustrate how Convolutional Neural Networks (CNNs) work. Each pass through the machine represents a layer in a CNN, where images are processed step by step. In CNNs,... each layer identifies specific features like edges, textures, or colors. Just as the pasta machine alters the photo with each pass, CNNs refine and simplify the image for better understanding. This step-by-step process allows CNNs to recognize complex images, making them useful in areas like image classification and object detection. It ain’t perfect but it’s a simple presentation.show more

@BrianRoemmele Brilliant analogy! The pasta machine's compression mirrors how CNNs use convolution filters, first described by Fukushima's Neocognitron (1980). Each 'layer' extracts increasingly abstract features, just as repeated passes create simpler image representations.

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Now you’ve got my brain thinking what it would look like for my body to pass through a machine like this. That’s how teleportation theorhetically works, right?

That's a weird degenerate and flawed man-made simulacrum of DNA transcription

Great illustration, indeed. Isn't it also how our brain sees images. It mixes the image from each eye, using a similar vertical grid, 24 times a second! I think is the reason we use grids for web designs and brochures and such.

He was a very good boy.

Super simple but it kinda blew my mind

They should rebrand CNNs

I have a feeling this is where the holographic angle comes in, no? And could we say that the way we encode and store memory is similar in that as the layers identify specifics we remember when and where and how we felt and the relationships each new stimulus impresses on us as we form a memory. ??

Fourier filters!

So the stimulus comes in and then we encode the whole thing in many places and in each place the memory is encoded to certain level respective to that areas ability and utility?