Editing Blog/2025-10-12/Word Magic (section)

==== A False Start ====

The first thought I had was about intermediate neuron layers and attempting to either slice off various layers of a network or to simply terminate the inference at some point. Intermediate neuron layer outputs are not meaningful on their own. You could interpret them as text after feeding some subset of them to a later layer in some combination and then 'convert to text' but that doesn't mean anything if the whole model was trained on something and you've just shaved off the last few layers. This doesn't seem particularly useful to think about, though, because nothing here fits well enough together. What does it mean to take out a layer? Where do the outputs go? Which ones do you link to which later ones with what weights? What does it mean to 'convert the vector to text'? Ironically, this seems like a nonsensical thought cul-de-sac.