Gray Area is being silly. I am quite aware of Probably Approximately Correct learning. Would you care to try to apply that theory to Einstein’s invention of General Relativity? PAC-learning theorems only work relative to a fixed model class about which we have no other information.
If you can see an apple fall, you already know enough to interpret the input to your webcam as an apple falling. This might require up to a dozen frames of environmental monitoring in order to notice all the objects there—the higher-resolution the webcame, the less time.
Think of Einstein, in a tiny box, thinking a million times as fast and much more cleanly, pondering each frame coming in off the webcam for a thousand years. At what point does he think the pixels might describe a permanent object? Perhaps before he has even seen two frames in succession—he can see many permanent objects just in the landscape of his own mind. At what point does he suspect a 3D world behind the 2D world? As soon as he sees two frames in succession. At what point does he suspect Galileo’s formula for gravity? Three frames in succession. At what point does he suspect this formula is universal? As soon as he sees blades of grass leaning over; plus it’s a very obvious hypothesis to the right kind of Bayesian. At what point does he suspect General Relativity? As soon as he notices locality of interaction as a principle applying to many things in the environment, and wonders, backed by a Judea-Pearl-like understanding of causality, if the locality principle is universally applied to the spatial organization induced from the webcam.
Gray Area is being silly. I am quite aware of Probably Approximately Correct learning. Would you care to try to apply that theory to Einstein’s invention of General Relativity? PAC-learning theorems only work relative to a fixed model class about which we have no other information.
If you can see an apple fall, you already know enough to interpret the input to your webcam as an apple falling. This might require up to a dozen frames of environmental monitoring in order to notice all the objects there—the higher-resolution the webcame, the less time.
Think of Einstein, in a tiny box, thinking a million times as fast and much more cleanly, pondering each frame coming in off the webcam for a thousand years. At what point does he think the pixels might describe a permanent object? Perhaps before he has even seen two frames in succession—he can see many permanent objects just in the landscape of his own mind. At what point does he suspect a 3D world behind the 2D world? As soon as he sees two frames in succession. At what point does he suspect Galileo’s formula for gravity? Three frames in succession. At what point does he suspect this formula is universal? As soon as he sees blades of grass leaning over; plus it’s a very obvious hypothesis to the right kind of Bayesian. At what point does he suspect General Relativity? As soon as he notices locality of interaction as a principle applying to many things in the environment, and wonders, backed by a Judea-Pearl-like understanding of causality, if the locality principle is universally applied to the spatial organization induced from the webcam.