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Playing with Vision Embeddings

prestonbjensen.com

1–10 of 18 posts

Re: Playing with Vision Embeddings

#3
Very nice visualizations, thanks for that!

One thing I still struggle with in my head is how these vision embeddings can then be used to give LLMs eyes.

Because you somehow need a giant training set which describes images in natural language, no? Is that actually how it works, or is there some smart trick so you don't need to pay labellers a bunch of money to look at pictures and describe them.

Re: Playing with Vision Embeddings

#4
post #3

Very nice visualizations, thanks for that! One thing I still struggle with in my head is how these vision embeddings can then be used to give LLMs eyes. Because you somehow need a giant training set which describes images in natural language, no? Is that actually how it works, or is there some smart trick so you don't need to pay labellers a bunch of money to look at pictures and describe them.

> Because you somehow need a giant training set which describes images in natural language, no?

That's definitely one way - they train a text encoder together with an image encoder on a labelled set of images. WL & 3b1b made a nice video on it: https://www.youtube.com/watch?v=iv-5mZ_9CPY

Re: Playing with Vision Embeddings

#5
post #3

Very nice visualizations, thanks for that! One thing I still struggle with in my head is how these vision embeddings can then be used to give LLMs eyes. Because you somehow need a giant training set which describes images in natural language, no? Is that actually how it works, or is there some smart trick so you don't need to pay labellers a bunch of money to look at pictures and describe them.

> Because you somehow need a giant training set which describes images in natural language, no? That's definitely one way - they train a text encoder together with an image encoder on a labelled set of images. WL & 3b1b made a nice video on it: https://www.youtube.com/watch?v=iv-5mZ_9CPY

Thanks I'll check out that video

Re: Playing with Vision Embeddings

#6
This reminds me of GANs and generating directly from a latent vector, as well as exploring them. I wonder how many of the original tricks used with GANs (like extrapolation stuff, optimizing for the latent vector to get a result etc) are easy to replicate with it.

Re: Playing with Vision Embeddings

#7
Beautiful illustrations I find, 'Playing' is just the free and motivated version of 'exploration'.

One thought on your nicely illustrated "key observation [is] that neural networks tend to place features along directions": my guess is that the neural net was TOLD to behave that way by choosing e.g. Cosine Loss?

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