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That weighted context is the 12228 dimensional vector, no?

I suppose that when you each element in the vector weighs 16 bits then the space is immense and capable to have a novel in a point.

GPT-4 is configurable up to 96 layers, each running their own embeddings. I think it was a business choice to afford the compute while they scale.

But if I understand correctly, GPT-4 reduces that to a 1536-dimensional vector. Roughly 1/8th. It's counterintuitive to me.