points by geraneum 2 days ago | 0 comments
There’s no such thing as a read/write head in transformers. You can use it as a metaphor but that’s a leaky metaphor, hence all these misunderstandings.
> In fact it has N read / write heads equal to the size of the context
And what is the asymptotic notation when computation scales linearly with the size of context?
> Either way, the simple truth is that you can train a transformer system
Which still doesn’t mean they have a read/write head or have O(1) complexity for token computation with “infinite context”.
The input to a transformer is a list of embeddings. The output is a list of embeddings of the same length. At the end of the day, you can represent the entirety of the transformer's matrix multiplies and such as a DFA (IEEE 754 float multiplication and addition is a simple DFA, and you're just scaling this up that many times). Thus, you take a list of embeddings (i.e., the tape) and output another, modified, list of embeddings. You have successfully read (ingested) and written (the transformer output) N positions on a tape.