Oddbean new post about login | logout Monosemantic rendering = polysemantic original?
I imagined it like a Fourier transform. Distilling individual features from a combined signal shared between multiple neurons. The reason you need to do this is the superposition hypothesis: that multiple neurons are encoding more features than just the orthogonal vectors.
Been actually brainstorming similar ideas - what is the difference between simple/axiomatic systems, or otherwise known as machines and Complex systems?. Complicated systems are fundamentally simple systems, but their own rules end up bumping up against each other. An LLM fundamentally based on Boolean logic, or instruction architecture scaling exponentially in FLOPS and energy use as the model gets more advanced, still a countable growth rate. A Complex System, being born, embedded and embodied within a coevolved ecosystem across millenia - the growth rate of interactions is almost like tetration, or some high order hyperoperator, maybe even approximating unaccountably many interactions. Some nostr brainstorming here. https://wikistr.com/semiotic-interaction*dc4cd086cd7ce5b1832adf4fdd1211289880d2c7e295bcb0e684c01acee77c06/cascading_semiotic_chains*dc4cd086cd7ce5b1832adf4fdd1211289880d2c7e295bcb0e684c01acee77c06/delta_interaction*dc4cd086cd7ce5b1832adf4fdd1211289880d2c7e295bcb0e684c01acee77c06
Ah, forgot to say why this is related! I'm arguing that the fundamental unit, or at least the most basic unit that can exist - the epsilon limit of meaning, is a delta-like interaction. An infinitesimally thin amount of time with some amplitude. The interaction creates some sort of response that is a wave. That wave will propagate as other interactions into other nearby neighborhoods, and also has a decay - which acts as a memory. The main point, experience is the convolution of delta interactions.
Chris kind of covers something along these lines. He argues these ai systems are fundamentally simple systems, like how we see uniformity across our brains. But this simple system can grow bigger and more complex abstractions. It’s quite beautiful when you think about it
Yeah, I'm doubtful you can make an argument about consciousness or 'thinking', because they're too loaded terms and often poorly defined. If you formalize meaning as interaction, things snap together so easily. Simple systems, even LLMs can only interact at the immediate distance. Complex Systems can interact, and find meaning with objects at nonzero distances. Any interaction that isn't desired needs to be changed, at either side. That change is learning/evolution in organic systems, while ML/AI is a computational approximation for everything because axiomatized systems are built with the enumerable rules for the sole context of their construction - the opposite of a complex one.