Earlier quoted context omitted.
The problem is, human intelligence is likely also based on a similar advanced chat bot setup. While GPT-4 only performs as good as top-10th percentile of human students taking an exam (a professional in the field can do much more than this), it is notable that as a generalist GPT-4 would outperform such professionals. And GPT-4 is much faster than a human. And we have not yet evaluated GPT-4 working in its optimal se…
Alas, if it could only remember and precisely relate more than 4k or 8k or 32k or 64k words... And if only scaling that context length weren't quadratic... Indeed, we would really expect an AI to be able to achieve AGI. And it might decide to do all kinds of alien things. The sky would not be the limit! We have more than 100 trillion synapses in our brains. That's not our "parameter" count. It's the size of the thing…
Agreed: LLM are just one of many necessary modules. But amazing nonetheless. The quadratic scaling problem needs an attentional-conceptual extractor layer with working memory. Hofstadter points out that this needs to be structured as a recursive “strange loop” (p 709 of GEB). Thalamo-cortico-thalamic circuitry is a strange loop and attentional self-control may happens by phase- or time-shifting activity of different circuits to achieve flexible “binding” for attention and compute.
I’m actually optimistic that this is not a heavy computational lift but a clever deep extension of recursive self-modulating algorithms across modules. The recursion is key. And the embodiment is also probably crucial to bootstrap self-consciousness. Watching infants bootstrap is an inspiration.