For example, Judea Pearl published the belief propagation algorithm in 1982. Why hadn’t someone already published it in 1962? Or 1922?
Belief propagation is the kind of thing that most people wouldn’t work on in an age before computers. It would be difficult to evaluate/test, but more importantly wouldn’t have much hope for application. Seems to me it arrived at a pretty normal time in our world.
For example, people have known for decades that flexible hierarchical planning is very important in humans but no one can get it to really work well in AI, especially in a reinforcement learning context.
Belief propagation is the kind of thing that most people wouldn’t work on in an age before computers. It would be difficult to evaluate/test, but more importantly wouldn’t have much hope for application.
Hmm. I’m not sure I buy that. Can’t we say the same thing about FFT? Doing belief prop by hand doesn’t seem much so different from doing an FFT by hand; and both belief prop and FFT were totally doable on a 1960s mainframe, if not earlier, AFAICT. But the modern FFT algorithm was published in 1965, and people got the gist of it in 1942, and 1932, and even Gauss in 1805 had the basic idea (according to wikipedia). FFTs are obviously super useful, but OTOH people do seem to find belief prop useful today, for various things, as far as I can tell, and I don’t see why they wouldn’t have found it useful in the 1960s as well if they had known about it.
What do you think of diffusion planning?
I think it’s interesting, thanks for sharing! But I have no other opinion about it to share. :)
If (for the sake of argument) Diffusion Planning is the (or part of the) long-sought-out path to getting flexible hierarchical planning to work well in practical AI systems, then I don’t think that would undermine any of the main points that I’m trying to make here. Diffusion Planning was, after all, (1) just published last year, (2) still at the “proof of principle / toy models” stage, and (3) not part of the existing LLM pipeline / paradigm.
Belief propagation is the kind of thing that most people wouldn’t work on in an age before computers. It would be difficult to evaluate/test, but more importantly wouldn’t have much hope for application. Seems to me it arrived at a pretty normal time in our world.
What do you think of diffusion planning?
Hmm. I’m not sure I buy that. Can’t we say the same thing about FFT? Doing belief prop by hand doesn’t seem much so different from doing an FFT by hand; and both belief prop and FFT were totally doable on a 1960s mainframe, if not earlier, AFAICT. But the modern FFT algorithm was published in 1965, and people got the gist of it in 1942, and 1932, and even Gauss in 1805 had the basic idea (according to wikipedia). FFTs are obviously super useful, but OTOH people do seem to find belief prop useful today, for various things, as far as I can tell, and I don’t see why they wouldn’t have found it useful in the 1960s as well if they had known about it.
I think it’s interesting, thanks for sharing! But I have no other opinion about it to share. :)
If (for the sake of argument) Diffusion Planning is the (or part of the) long-sought-out path to getting flexible hierarchical planning to work well in practical AI systems, then I don’t think that would undermine any of the main points that I’m trying to make here. Diffusion Planning was, after all, (1) just published last year, (2) still at the “proof of principle / toy models” stage, and (3) not part of the existing LLM pipeline / paradigm.