• 0 Posts
  • 36 Comments
Joined 3 years ago
cake
Cake day: June 30th, 2023

help-circle
  • Easier said than done. That’s kind of the purpose of an individual neuron approach I think. I don’t see a way that a bulk retrain is reasonable because it takes a long time, uses a lot of resources, and also requires you to have your whole training corpus handy all the time. Your brain is not doing a wholesale rewrite for every new memory, and new memories often chain together. I don’t think you can just say “ah well, let’s update the RAG or do another supervised fine tune with LoRA or something”. At present, we just don’t really have the machinery in the models to do simultaneous learning, inference, and forward planning.


  • I’m not a neurologist or a philosopher so I think this may not be something I can speak intelligently about, but it seems to me that the question doesn’t really live in the function approximation, but in the gaps. Doing a single train of thought is the easy part. I think what you need is an “always online” feature to keep thinking and some way to be stateful (make memories) without constantly retraining the whole network or whole sets of layers.

    This is, I think, the benefit of the parallelism and asynchrony of the “individual neuron” discussed in the book.