| I like the process that goes into these "imagine the architecture of AGI" articles. It's all hypothetical, but it's really fun. But it's a missed opportunity if you don't embed LLMs in some of the core modules -- and highlight where they excel. LLMs aren't identical to any part of the human brain, but they do a remarkable job of emulating elements of human cognition: language, obviously, but also many types of reasoning and idea exploration. Where LLMs fail is in lookup, memory, and learning. But we've all seen how easy it is to extend them with RAG architectures. My personal, non-scientific prediction for the basic modules of AGI are: - LLMs to do basic reasoning - a scheduling system that runs planning and execution tasks - sensory events that can kick off reasoning, but with clever filters and shortcuts - short term memory to augment and improve reasoning - tools (calculators etc.) for common tasks - a flexible and well _designed_ memory system -- much iteration required to get this right, and i don't see a lot of work being done on it, which is interesting - finally, a truly general intelligence would have the capability to mutate many of the above elements based on learning (LLM weights, scheduling parameters, sensory filters, and memory configurations). But not everything needs to be mutable. many elements of human cognition are probably immutable as well. |
I'd try the idea myself, but I have a job. :-)