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Comment by dicroce | Hacker News Reader

What about synthetic data that is correct? Example: Using the output of a physics simulation to train... The output is synthetic (as in, its not from the real world) but it is governed by the equations of motion...

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Going from the parent comment's assertion, the answer would be that if you want to train something to predict physics, the original physics simulation that's generating the data is either:

1. Already doing that, in which case it's already the superior model.

2. Not doing that correctly, in which case the synthetic data output is equally poor.

Consider computer graphics and computer vision. If you had a photorealistic renderer, it could be useful for generating training data for a vision algorithm. However, you can't just run your rendering pipeline backwards to create a scene out of an image.

I mean, if (1) is true but you get faster performance, then it's useful, right?

Yes. A typical example would be the use of statistical emulators, emulating process (physical) based models that are computationally complex in the environmental sciences.

This is the one that seems to be useful today. Running simulations with physics being modeled across objects seems to be useful for reinforcement learning algorithms that interact in the real world. You see some of this with autonomous vehicle training, robot manipulation training, etc. I think there are also emergent interactions that can occur that you wouldn't have modeled directly unless you let the simulation run.

The point lalaland1125 is making is that the equations of motion are the existing superior model in this scenario.

Right, but presumably we don't want the model to learn those, since they're an impractically low-level model. If you're training an AI for flying a plane, you want it to learn "the simplest model that works"—presumably something like aerodynamics—not a far more computationally-intensive (and data-intensive!) model, like e.g. quantum chromodynamics.

The example is fundamentally different as physics simulations have closed form solutions or can be numerically approximated for various initial and boundary conditions. Therefore, by definition the generation is not synthetic.

Other examples I could think of fall in the category the top comment is referring to.

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