7 ms·

The reason I ask is because I feel that a memory model is one of the major bottlenecks toward AGI.

• pmalynin 3y ago
  On a more serious note, I do agree with you that memory and self-excitation seem like they are the last push thats needed to get to something more akin to "AGI". But I don't think that Rubicon will be crossed with plugins.
  • MacsHeadroom 3y ago
    >I do agree with you that memory and self-excitation seem like they are the last push thats needed to get to something more akin to "AGI" "We show that transformer-based large language models are computationally universal when augmented with an external memory. Any deterministic language model that conditions on strings of bounded length is equivalent to a finite automaton, hence computationally limited. However, augmenting such models with a read-write memory creates the possibility of processing arbitrarily large inputs and, potentially, simulating any algorithm." From "Memory Augmented Large Language Models are Computationally Universal" https://deepai.org/publication/memory-augmented-large-language-models-are-computationally-universal https://deepai.org/publication/memory-augmented-large-langua...
• nunodonato 3y ago
  why? short and long-term memory is really easy to do. Even my own basic assistant has it (running on fine-tuned curie model)