• Author here.

    I spent the last weekend thinking about continual learning. A lot of people think that we can solve long term memory and learning in LLMs by simply extending the context length to infinity. I analyse a different perspective that challenges this assumption.

    Let me know how you think about this.

    • Your conclusion touches on this, but I think the brain analogy is stronger than the hardware/software dichotomy.

      It is also my very uninformed intuition: https://news.ycombinator.com/item?id=44910353

      Also interesting to think about: could a single system be generally intelligent, or is a certain bias actually a power. Can we have billions of models, each with their own "experience"

    • > Let me know how you think about this.

      Well, I think of every Large Language Model as if it were a spectacularly faceted diamond.

      More on these lines in a recent-ish "thinking in public" attempt by yours truly, lay programmer, to interpret what an LLM-machine might be.

      Riff: LLMs are Software Diamonds

      https://www.evalapply.org/posts/llms-are-diamonds/