So I think this is a very interesting post which may not be beng appreciated as much because the main example is a fictonal one (albeit from a very excellent pair of books). I’d like to give a different example stolen from research that my former college roomate is now doing: We can predict the individual behavior of a water molecule to a very rough approximation from first principles. But as soon as one has more than one molecule predicting very basic questions like “what should the boiling and cooling temperatures be?” “what should the index of refraction be?” “what sort of crystals should I expect to form when I cool it?” are computationally infeasible. So a lot of physicists are working on questions like this but essentially trying to simplify the computations and figure out which approximatons you can get away with and which don’t quite work.
In this context, this is an example where to use the sort of analogy in the post, knowing the name of the substance really doesn’t pay rent very directly since the computations are just too arduous. Quantum mechanics can pay rent in other ways, but using it to pay rent for this purpose seems to be difficult.
Also note that being able to pay rent to be able to predict something is still not the same as being able to control it. Kvothe might be able to know where every molecule of air is and be able to compute where they are going (ignoring for a moment issues of fundamental uncertainty due to quantum mechanical issues), but that doesn’t mean one can figure out an action that will make the air do what one wants. To do that requires not just computing a single path of events but likely requires computing many paths and figuring out which one one wants. Similarly, the evil oracle has a much tougher job computationally than a regular oracle.
Also note that being able to pay rent to be able to predict something is still not the same as being able to control it. Kvothe might be able to know where every molecule of air is and be able to compute where they are going (ignoring for a moment issues of fundamental uncertainty due to quantum mechanical issues), but that doesn’t mean one can figure out an action that will make the air do what one wants. To do that requires not just computing a single path of events but likely requires computing many paths and figuring out which one one wants. Similarly, the evil oracle has a much tougher job computationally than a regular oracle.
Conversely, in many cases, e.g., simple chaotic systems, it is easier to control something then to predict what will happen if you don’t intervene.
good point on the control. I did try to emphasize the prediction aspect with the sword tree example instead of like the felurian or ambrose scenes, which are impossible.
But some belief algorithms can pay rent in “superpowers” I think. There are things much easier to control than awful nonlinear fluid dynamics.
Edit: also, do you think in possible future versions of this concept I should avoid the fictional examples?
The point of bringing up fictional examples was that it is actually a really good example of what I’m talking about and some people are familiar with it.
Care to name a few that you think can be “superpowers”?
I have no objection to using fictional examples, especially when it illustrates a point perfectly. Just be sure to buffer it with real-world examples. You did a good job mentioning occupations that can viscerally feel physics. I did find it rather surprising that you didn’t mention basketball players’ understanding of parabolas. That was the first example I thought of right after reading the word “machinist”.
superpowers is a bit of an exaggeration. I don’t know many we can get gains in, but having a more intuitive than mathematical understanding of everyday physics should lead to some interesting abilities. For example, derivable from solid mechanics equations is the fact that a shallow cut on the back of a wood beam will allow you to break it with maybe 1⁄3 of the force. More brittle materials work even better. I’m sure there are others. I’ll keep thinking.
The basketball example is a really good one, thanks.
For example, derivable from solid mechanics equations is the fact that a shallow cut on the back of a wood beam will allow you to break it with maybe 1⁄3 of the force. More brittle materials work even better.
Holy crap! That’s awesome!
I’ve taken a metal smithing class for several semesters, and noticed that an understanding of the physics involved makes one much better at producing the results desired. The teacher has an excellent balance of knowledge and feeling-about-the-knowledge. It is an admirable trait, feeling what you know.
Edit: also, do you think in possible future versions of this concept I should avoid the fictional examples? The point of bringing up fictional examples was that it is actually a really good example of what I’m talking about and some people are familiar with it.
Can you make the point with non-fictional examples? If not, then it seems like generalizing from fictional evidence. A lot of what Kvothe can do is simply intractable, and so using him as an example seems like magical thinking rather than someone familiar with real-world optimization models.
So I think this is a very interesting post which may not be beng appreciated as much because the main example is a fictonal one (albeit from a very excellent pair of books). I’d like to give a different example stolen from research that my former college roomate is now doing: We can predict the individual behavior of a water molecule to a very rough approximation from first principles. But as soon as one has more than one molecule predicting very basic questions like “what should the boiling and cooling temperatures be?” “what should the index of refraction be?” “what sort of crystals should I expect to form when I cool it?” are computationally infeasible. So a lot of physicists are working on questions like this but essentially trying to simplify the computations and figure out which approximatons you can get away with and which don’t quite work.
In this context, this is an example where to use the sort of analogy in the post, knowing the name of the substance really doesn’t pay rent very directly since the computations are just too arduous. Quantum mechanics can pay rent in other ways, but using it to pay rent for this purpose seems to be difficult.
Also note that being able to pay rent to be able to predict something is still not the same as being able to control it. Kvothe might be able to know where every molecule of air is and be able to compute where they are going (ignoring for a moment issues of fundamental uncertainty due to quantum mechanical issues), but that doesn’t mean one can figure out an action that will make the air do what one wants. To do that requires not just computing a single path of events but likely requires computing many paths and figuring out which one one wants. Similarly, the evil oracle has a much tougher job computationally than a regular oracle.
Conversely, in many cases, e.g., simple chaotic systems, it is easier to control something then to predict what will happen if you don’t intervene.
good point on the control. I did try to emphasize the prediction aspect with the sword tree example instead of like the felurian or ambrose scenes, which are impossible.
But some belief algorithms can pay rent in “superpowers” I think. There are things much easier to control than awful nonlinear fluid dynamics.
Edit: also, do you think in possible future versions of this concept I should avoid the fictional examples? The point of bringing up fictional examples was that it is actually a really good example of what I’m talking about and some people are familiar with it.
Care to name a few that you think can be “superpowers”?
I have no objection to using fictional examples, especially when it illustrates a point perfectly. Just be sure to buffer it with real-world examples. You did a good job mentioning occupations that can viscerally feel physics. I did find it rather surprising that you didn’t mention basketball players’ understanding of parabolas. That was the first example I thought of right after reading the word “machinist”.
superpowers is a bit of an exaggeration. I don’t know many we can get gains in, but having a more intuitive than mathematical understanding of everyday physics should lead to some interesting abilities. For example, derivable from solid mechanics equations is the fact that a shallow cut on the back of a wood beam will allow you to break it with maybe 1⁄3 of the force. More brittle materials work even better. I’m sure there are others. I’ll keep thinking.
The basketball example is a really good one, thanks.
Holy crap! That’s awesome!
I’ve taken a metal smithing class for several semesters, and noticed that an understanding of the physics involved makes one much better at producing the results desired. The teacher has an excellent balance of knowledge and feeling-about-the-knowledge. It is an admirable trait, feeling what you know.
Can you make the point with non-fictional examples? If not, then it seems like generalizing from fictional evidence. A lot of what Kvothe can do is simply intractable, and so using him as an example seems like magical thinking rather than someone familiar with real-world optimization models.
It wasn’t supposed to be evidence. It was an “alice and bob”-type illustration story that happens to exist in fiction.
I’ll use better examples in future tho.