7 ms·

in some sense yes, and if you are only interested in good predictions this might work out well. What, maybe due to my limited understanding, is, that this is no

in some sense yes, and if you are only interested in good predictions this might work out well. What, maybe due to my limited understanding, is, that this is not theory driven and therefore does not really provide understanding of the underlying process.

bongodongobob 2y ago
I think we understand the processes just fine. The issue is that we can't get a "closed form" solution for 10^100 interactions per planck time.
- gowld 2y ago
  That's like saying chemistry has nothing to understand because we know Schrodinger's wave equation. Or that we understand biology and psychology just for for the same reason.
  - bongodongobob 2y ago
    Yeah, I think that makes sense. Those systems are similar in that they are made of zillions of tiny parts and there's no way to pull a one equation to rule them all out of it. We could, given infinite compute, but it's just not feasible.
Mathnerd314 2y ago
I think at some point it is worth admitting that there are variables you can't account for. Like the precise geography - the models model an area 1 mile square as a single vector, maybe even more coarse. They don't model every tree, rock, and bush. In a neural net you can just have "weight goop" which accounts for the net effect of these unmodeled features, but in a traditional model adding "fudge factors" and extrapolating back from the model to points of interest is tricky.
nico 2y ago
> and therefore does not really provide understanding of the underlying process What is “the underlying process”? For example, Newton was able to model gravity quite successfully without ever being able to “understand the underlying process”. In fact, physics today still doesn’t have a good grasp on what gravity is. Yet we use the models and equations all the time In a way, physics is also a collection of black boxes, perhaps just seemingly more elegant boxes
- lainga 2y ago
  > What is “the underlying process”? IMO - The simple ones: advection, latent heat release/absorption from water changing phases, and the Coriolis force. If you need an AI for this, please take a course on differential equations. The hard ones: droplet/ice crystal formation, cloud feedback on radiative transfer, evaporation at air-sea boundaries. If you can train a model for these processes, please, please tell someone.
  - danielmarkbruce 2y ago
    "what is the underlying process" is another way of saying, all we have is models. We don't really understand anything. Even gravity. Yet, we can model gravity extremely well for practical purposes.
    - nico 2y ago
      Exactly. Taking it further, I don’t understand how my hands work. Yet here I am typing away, without even having a good model for it, except just the language I’m using to describe what I’m doing
- SaberTail 2y ago
  Gravity can be modeled as "things on the earth's surface accelerate downward at about 10 m/s², regardless of their mass". This works very well. Gravity can be modeled as "planets orbit the sun according to Kepler's laws". This also works very well. Newton realized that these phenomena could be explained as arising from the same underlying process of an inverse square law. This is a much more useful model, and allows predictions that allow us to do things like space flight, even if it is not complete.
MyFirstSass 2y ago
Wouldn't you be able to somehow couple it with another model that takes the NN data and somehow untangles it's convoluted logic into an isomorphic human readable equation, ie. a model that has one task and that is translating NN logic into human equations. The training data could be real physics in a simulator held up against evolutionary driven AI logic that competes against it with various goals that are then evaluated and if given a high score then marked as isomorphic and given enough runs you'd get a dataset.
- nico 2y ago
  Very cool idea! I wonder how simple could the NNs be to model some basic physical process?

bongodongobob 2y ago

I think we understand the processes just fine. The issue is that we can't get a "closed form" solution for 10^100 interactions per planck time.

gowld 2y ago
That's like saying chemistry has nothing to understand because we know Schrodinger's wave equation. Or that we understand biology and psychology just for for the same reason.
- bongodongobob 2y ago
  Yeah, I think that makes sense. Those systems are similar in that they are made of zillions of tiny parts and there's no way to pull a one equation to rule them all out of it. We could, given infinite compute, but it's just not feasible.

Mathnerd314 2y ago

I think at some point it is worth admitting that there are variables you can't account for. Like the precise geography - the models model an area 1 mile square as a single vector, maybe even more coarse. They don't model every tree, rock, and bush. In a neural net you can just have "weight goop" which accounts for the net effect of these unmodeled features, but in a traditional model adding "fudge factors" and extrapolating back from the model to points of interest is tricky.

nico 2y ago

> and therefore does not really provide understanding of the underlying process What is “the underlying process”? For example, Newton was able to model gravity quite successfully without ever being able to “understand the underlying process”. In fact, physics today still doesn’t have a good grasp on what gravity is. Yet we use the models and equations all the time In a way, physics is also a collection of black boxes, perhaps just seemingly more elegant boxes

lainga 2y ago
> What is “the underlying process”? IMO - The simple ones: advection, latent heat release/absorption from water changing phases, and the Coriolis force. If you need an AI for this, please take a course on differential equations. The hard ones: droplet/ice crystal formation, cloud feedback on radiative transfer, evaporation at air-sea boundaries. If you can train a model for these processes, please, please tell someone.
- danielmarkbruce 2y ago
  "what is the underlying process" is another way of saying, all we have is models. We don't really understand anything. Even gravity. Yet, we can model gravity extremely well for practical purposes.
  - nico 2y ago
    Exactly. Taking it further, I don’t understand how my hands work. Yet here I am typing away, without even having a good model for it, except just the language I’m using to describe what I’m doing
SaberTail 2y ago
Gravity can be modeled as "things on the earth's surface accelerate downward at about 10 m/s², regardless of their mass". This works very well. Gravity can be modeled as "planets orbit the sun according to Kepler's laws". This also works very well. Newton realized that these phenomena could be explained as arising from the same underlying process of an inverse square law. This is a much more useful model, and allows predictions that allow us to do things like space flight, even if it is not complete.

MyFirstSass 2y ago

Wouldn't you be able to somehow couple it with another model that takes the NN data and somehow untangles it's convoluted logic into an isomorphic human readable equation, ie. a model that has one task and that is translating NN logic into human equations. The training data could be real physics in a simulator held up against evolutionary driven AI logic that competes against it with various goals that are then evaluated and if given a high score then marked as isomorphic and given enough runs you'd get a dataset.

nico 2y ago
Very cool idea! I wonder how simple could the NNs be to model some basic physical process?