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PHphkahler40분 전
If it can be made orthogonal, can you go a step further and diagonalize it? The storage and performance improvement from that would be huge.
BIBirbSingularity7시간 전
I can't help but think of orthogonal frequency-division multiplexing and it's use in encoding data on multiple carrier frequencies, and it makes me wonder what other parallels we will discover between digital transmission technology for cross-domain stuff like this.
HAharveyrook59분 전
Now I’m wondering what is the eigenspace of an LLM? If I take a set of LLM’s with the same number of parameters, then what are the eigenvectors? Do they have different personalities?
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If it can be made orthogonal, can you go a step further and diagonalize it? The storage and performance improvement from that would be huge.
I can't help but think of orthogonal frequency-division multiplexing and it's use in encoding data on multiple carrier frequencies, and it makes me wonder what other parallels we will discover between digital transmission technology for cross-domain stuff like this.
Now I’m wondering what is the eigenspace of an LLM? If I take a set of LLM’s with the same number of parameters, then what are the eigenvectors? Do they have different personalities?
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