Worth noting this Socratic review of Sir Penrose's theory of quantum minds is by Dr Hans Moravec, an important roboticist and AI theorist, widely known for Moravec's Paradox :
"it is comparatively easy to make computers exhibit adult level performance on intelligence tests or playing checkers, and difficult or impossible to give them the skills of a one-year-old when it comes to perception and mobility."[1]
which began the shift in paradigms exemplified by the behaviour based & embodied robotics movements.
[1] Dr Hans Moravec, snipped from http://www.eugenewei.com/blog/2014/10/13/moravecs-paradox-and-self-driving-cars
Playing checkers seems like a well-defined task to accomplish. A computer that has "the skills of a one-year-old when it comes to perception and mobility." is not defined at all. Mobility? Perceiving what?
Im reminded of the multimillion dollar AI-based image recognition system the military developed, in the 80s or 90s to analyze images looking for tanks. When the system was tested on photos, that were not from their pool of stock test photos used to train the systems, it got almost 100% wrong. Why? Because they stock photos had well-composed shots on a sunny day with some clouds (usually the spots tanks are hidden in are overcast or very cloudy). The "real" shots were all cloudy (as expected) and the system had actually been trained to recognize discrete clouds rather than Tanks.
Perception is about distinguishing, imagining physical properties (this can be disassembled or just casually appears composite due to perspective), judging and guessing at unseen properties. I figure an pool ball has a curved 3d spherical shape, because I've seen one before and felt it. At the same time I imagine that there is no "top" or differing feature anywhere on the ball, based on the appearance of what portion I can see (it looks clear and flat white? i expect the rest to be so).
To clarify, Moravec was speaking of robots, e.g. embodied computation.
Moravec's paradox, though it now seems obvious, was the opposite of the prevailing view.
It implies that if 'being in the world' (mobility, perception & grasping) are the hard tasks then this is where AI will emerge not in simulation, planning or board games.
My memory is failing me, but I think I heard a talk once where a (specific?) robot motion-planning problem is PSPACE-hard, aka in a class that contains the problems in NP. Maybe that's another way to articulate Moravec's paradox.
This is only tangentially related but I hope it provokes discussion. One thing that I don't understand is why Platonism remains extremely popular throughout Mathematics departments the world over and Finitism/Ultra-finitism is so unpopular with them. Combinatorics and Discrete topics are often very unpopular topics to work on in my experience.
Finitism in an analogous way to functional programming seems like the best way to move the field forward, but it is rarely used by Mathematicians in practice. Why on earth is this? (My understanding of mathematics is lacking, so I hope this doesn't come off as a silly comment)
I'm having a hard time understanding this comment. Are you talking about mathematics or philosophy?
I don't understand why finitism would ever be expected to lead to new mathematical insights, since it basically amounts to closing off research directions because they don't have some nebulous quality of "real-ness". I also don't see how finitism has any connection to functional programming.
Ultra-finitist logic is a perfectly rigorous field of study in its own right. I think OP is making a point that this logic and us related branches are quite understudied.
It's encouraging to note that with things like Homotopty Type Theory, we're finally starting to come to grips with Fundamentals that aren't tied to the ZFC implementation.
But ultrafinitism isn't actually interesting as a mathematical theory. As the previous poster said, its appeal lies in its "realness". Intuitionistic and linear logic are substantially more interesting.
But this was why I posed it as a question, everyone says this is somehow 'more interesting' but is that because it is actually qualitatively more interesting or are more interesting things coming out of it simply due to the fact that it is more popular quantitatively with researchers? If it is qualitatively more interesting, what about it makes it so?
I likened it to functional programming because finitism makes things interesting via its purity and restriction in an analogous way.
16 comments
[ 5.6 ms ] story [ 56.8 ms ] thread"it is comparatively easy to make computers exhibit adult level performance on intelligence tests or playing checkers, and difficult or impossible to give them the skills of a one-year-old when it comes to perception and mobility."[1]
which began the shift in paradigms exemplified by the behaviour based & embodied robotics movements.
Perception is about distinguishing, imagining physical properties (this can be disassembled or just casually appears composite due to perspective), judging and guessing at unseen properties. I figure an pool ball has a curved 3d spherical shape, because I've seen one before and felt it. At the same time I imagine that there is no "top" or differing feature anywhere on the ball, based on the appearance of what portion I can see (it looks clear and flat white? i expect the rest to be so).
Moravec's paradox, though it now seems obvious, was the opposite of the prevailing view.
It implies that if 'being in the world' (mobility, perception & grasping) are the hard tasks then this is where AI will emerge not in simulation, planning or board games.
Finitism in an analogous way to functional programming seems like the best way to move the field forward, but it is rarely used by Mathematicians in practice. Why on earth is this? (My understanding of mathematics is lacking, so I hope this doesn't come off as a silly comment)
I don't understand why finitism would ever be expected to lead to new mathematical insights, since it basically amounts to closing off research directions because they don't have some nebulous quality of "real-ness". I also don't see how finitism has any connection to functional programming.
It's encouraging to note that with things like Homotopty Type Theory, we're finally starting to come to grips with Fundamentals that aren't tied to the ZFC implementation.
I likened it to functional programming because finitism makes things interesting via its purity and restriction in an analogous way.
https://news.ycombinator.com/newsguidelines.html