March 28, 2024, 10:29 a.m. | /u/Alarming-Ad8154

Machine Learning

I have an (probably dumb) idea for long term transformer memory.

You can embed sentences into vectors of length \~128 - \~2048 right? Then you can cluster those sentences and effectively project them into lower dimensional spaces.

I have often wondered whether you could take \~50.000 cardinal points in the embedding space (points such that the summed of squared distance to all sentences in a representative corpus is minimal). You'd then map each sentence in a big corpus to the …

cluster embed machinelearning memory project spaces them token transformer vectors

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