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prolyxis | 1 year ago
- the language network, which delivers formal linguistic competence - the multiple demand network, which provides reasoning ability - the default network, which tracks narratives above the clause level - the theory of mind network, which infers the mental state of another entity
This leads to their argument that a modular structure would lead to enhanced ability for an LLM to be both formally and functionally competent. (While LLMs currently exhibit human-level formal linguistic competence, their functional competence--the ability to navigate the real world through language--has room for improvement.)
Transformer models, they note, have degree of emergent modularity through "allowing different attention heads to attend to different input features."
I was wondering, is it possible to characterize the degree of emergent modularity in current systems?
imtringued|1 year ago
This is basically no different from a Turing machine going from one tape to multiple tapes. While in theory it doesn't make the Turing machine more powerful, it saves a whole lot of book keeping operations that are necessary to work around the limitations of a single tape.
Another limitation is the inability to seek to positions by moving the head back and forth to rewrite old data in the context.
JieJie|1 year ago
"We also find more abstract features—responding to things like bugs in computer code, discussions of gender bias in professions, and conversations about keeping secrets."
1: https://www.anthropic.com/research/mapping-mind-language-mod...
ithkuil|1 year ago