The interesting thing to me about the question, “Will we need a new paradigm for AGI?” is that a lot of people seem to be focused on this but I think it misses a nearby important question.
As we get closer to a complete AGI, and start to get more capable programming and research assistant AIs, will those make algorithmic exploration cheaper and easier, such that we see a sort of ‘Cambrian explosion’ of model architectures which work well for specific purposes, and perhaps one of these works better at general learning than anything we’ve found so far and ends up being the architecture that first reaches full transformative AGI?
The point I’m generally trying to make is that estimates of software/algorithmic progress are based on the progress being made (currently) mostly by human minds. The closer we get to generally competent artificial minds, the less we should expect past patterns based on human inputs to hold.
I generally agree, i just have some specific evidence which I believe should adjust estimates in the report towards expecting more accessible algorithmic improvements than some people seem to think.
The interesting thing to me about the question, “Will we need a new paradigm for AGI?” is that a lot of people seem to be focused on this but I think it misses a nearby important question.
As we get closer to a complete AGI, and start to get more capable programming and research assistant AIs, will those make algorithmic exploration cheaper and easier, such that we see a sort of ‘Cambrian explosion’ of model architectures which work well for specific purposes, and perhaps one of these works better at general learning than anything we’ve found so far and ends up being the architecture that first reaches full transformative AGI?
The point I’m generally trying to make is that estimates of software/algorithmic progress are based on the progress being made (currently) mostly by human minds. The closer we get to generally competent artificial minds, the less we should expect past patterns based on human inputs to hold.
Tom Davidson’s work on a compute-centric framework for takeoff speed is excellent, IMO.
I generally agree, i just have some specific evidence which I believe should adjust estimates in the report towards expecting more accessible algorithmic improvements than some people seem to think.