4 ms·
> how llms map to the brain For the lower level - word embedings (word2vec, "King – Man + Woman = Queen") - one can see a similarity https://www.nature.com/ar
by trhway 2y ago
> how llms map to the brain
For the lower level - word embedings (word2vec, "King – Man + Woman = Queen") - one can see a similarity
https://www.nature.com/articles/d41586-019-00069-1 https://www.nature.com/articles/d41586-019-00069-1 and
https://gallantlab.org/viewer-huth-2016/ https://gallantlab.org/viewer-huth-2016/
"The map reveals how language is spread throughout the cortex and across both hemispheres, showing groups of words clustered together by meaning."
- nyrikki 2y agoThat is the latent space. Very different from a feed forward network with perceptrons, auttograd, etc... Inner product spaces are fixed points, mapping between models is less surprising because the general case is a merger set IIRC.