6 ms·

Computer model matches humans at predicting how objects move

63 points by tekromancr 10y ago

grondilu 10y ago
Video games could use something like that. Especially for collisions. Games often struggle to do them correctly and completely absurd results are not rare.
- ne0phyte 10y ago
  Game physics engines update their objects (acceleration, collision, constraints/joints etc) only so often at a certain tick rate to leave enough cpu time for other things. You can have very precise and realistic physics simulations already - they just don't run at realtime. I don't think this is a solution for bad physics in games.
  - Razengan 10y ago
    Whatever happened to dedicated physics processors? Can't we have a separate physical unit doing all those calculations in realtime?
    - ss248 10y ago
      >Whatever happened to dedicated physics processors? Nvidia bought PhysX and stopped production of dedicated PPU. PhysX is just software now. And because it's proprietary (no AMD cards support/CPU implementation is slow) we don't really see games build around it.
      - goldenkey 10y ago
        GPUs or CPUs can be designated as PhysX devices within the NVIDIA drivers. Im not sure if that rules out using AMD devices but probably.
- CoryG89 10y ago
  The idea here isn't making better collision simulations. We do that well enough already. I think the big deal here is teaching an AI how to predict the outcomes of collisions by training it with a physics engine.
carapace 10y ago
http://www.csail.mit.edu/computer_model_matches_humans_predicting_how_objects_move http://www.csail.mit.edu/computer_model_matches_humans_predi...
Animats 10y ago
Finally! This is a big step forward in common sense reasoning. Robots need this.
deleted 10y ago
[deleted]
joe_the_user 10y ago
The thing is that I don't think what humans are good at is statically predicting the movement of objects from video. Rather, I think the strong human skill is reacting appropriately and quickly to movements.
- jamesrcole 10y ago
  I don't think you could react quickly to something without having predicted the behavior of that thing in advance.
  - LionessLover 10y ago
    Depends on what you mean by "predict". Also, unfortunately I don't even remember where I saw or heard this in a lecture, but when studying neuroscience I remember to have seen exactly this question and an example showing that you actually don't have to make predictions. I also forgot the explanation that showed how the (real, biological) neural network solves just such a problem without having to make a prediction. I only have the fuzziest memory of it being a process and at no point was there any prediction of the path of the object being tracked. It was just matching several sensory signal inputs and creating outputs, something clever, using an indirect approach. "Predicting" would be observing the object for x amount of time, doing a calculation where it will be some time later, using a model to come up with a way to intercept, then creating outputs, all of that in a loop, something like that. In any case, the way the neural network actually solved it was completely different from how an engineer would do it. In a sense, the neural network was "cheating" and doing far less work than you would expect. The one thing I do remember for sure was there was no "prediction" involved - none at all. Unless you argue backwards and say because it succeeded you declare the process a "prediction". Once explained the whole process was actually quite primitive. Again, that was research on an actual biological neural network. Darn, now I wish I had paid more attention. Any actual neuroscientists here? Without the details even I myself can't see my own comment as a satisfactory reply, but only as a step to actually getting one from somewhere or someone else. But note that it depends on what you mean by "prediction" - as I said, if you define it backwards from success than sure, prediction happened. My point is that the process is very different from how a human-made algorithm would do it.
nharada 10y ago
Paper: http://www.mit.edu/~ilkery/papers/phys_nips.pdf http://www.mit.edu/~ilkery/papers/phys_nips.pdf
- eli_gottlieb 10y ago
  Aka: "Another probabilistic programming paper." They hacked on a 3D physics engine to make it capable of Monte Carlo sampling and inference, and then stuck a deep neural net on the front to do some parameter inference more easily.
tudorw 10y ago
Finally, we can build a robot that can play a game of peepo :)

63 points by tekromancr 10y ago

Video games could use something like that. Especially for collisions. Games often struggle to do them correctly and completely absurd results are not rare.

ne0phyte 10y ago
Game physics engines update their objects (acceleration, collision, constraints/joints etc) only so often at a certain tick rate to leave enough cpu time for other things. You can have very precise and realistic physics simulations already - they just don't run at realtime. I don't think this is a solution for bad physics in games.
- Razengan 10y ago
  Whatever happened to dedicated physics processors? Can't we have a separate physical unit doing all those calculations in realtime?
  - ss248 10y ago
    >Whatever happened to dedicated physics processors? Nvidia bought PhysX and stopped production of dedicated PPU. PhysX is just software now. And because it's proprietary (no AMD cards support/CPU implementation is slow) we don't really see games build around it.
    - goldenkey 10y ago
      GPUs or CPUs can be designated as PhysX devices within the NVIDIA drivers. Im not sure if that rules out using AMD devices but probably.
CoryG89 10y ago
The idea here isn't making better collision simulations. We do that well enough already. I think the big deal here is teaching an AI how to predict the outcomes of collisions by training it with a physics engine.

carapace 10y ago

http://www.csail.mit.edu/computer_model_matches_humans_predicting_how_objects_move http://www.csail.mit.edu/computer_model_matches_humans_predi...

Animats 10y ago

Finally! This is a big step forward in common sense reasoning. Robots need this.

deleted 10y ago

[deleted]

joe_the_user 10y ago

The thing is that I don't think what humans are good at is statically predicting the movement of objects from video. Rather, I think the strong human skill is reacting appropriately and quickly to movements.

jamesrcole 10y ago
I don't think you could react quickly to something without having predicted the behavior of that thing in advance.
- LionessLover 10y ago
  Depends on what you mean by "predict". Also, unfortunately I don't even remember where I saw or heard this in a lecture, but when studying neuroscience I remember to have seen exactly this question and an example showing that you actually don't have to make predictions. I also forgot the explanation that showed how the (real, biological) neural network solves just such a problem without having to make a prediction. I only have the fuzziest memory of it being a process and at no point was there any prediction of the path of the object being tracked. It was just matching several sensory signal inputs and creating outputs, something clever, using an indirect approach. "Predicting" would be observing the object for x amount of time, doing a calculation where it will be some time later, using a model to come up with a way to intercept, then creating outputs, all of that in a loop, something like that. In any case, the way the neural network actually solved it was completely different from how an engineer would do it. In a sense, the neural network was "cheating" and doing far less work than you would expect. The one thing I do remember for sure was there was no "prediction" involved - none at all. Unless you argue backwards and say because it succeeded you declare the process a "prediction". Once explained the whole process was actually quite primitive. Again, that was research on an actual biological neural network. Darn, now I wish I had paid more attention. Any actual neuroscientists here? Without the details even I myself can't see my own comment as a satisfactory reply, but only as a step to actually getting one from somewhere or someone else. But note that it depends on what you mean by "prediction" - as I said, if you define it backwards from success than sure, prediction happened. My point is that the process is very different from how a human-made algorithm would do it.

nharada 10y ago

Paper: http://www.mit.edu/~ilkery/papers/phys_nips.pdf http://www.mit.edu/~ilkery/papers/phys_nips.pdf

eli_gottlieb 10y ago
Aka: "Another probabilistic programming paper." They hacked on a 3D physics engine to make it capable of Monte Carlo sampling and inference, and then stuck a deep neural net on the front to do some parameter inference more easily.

tudorw 10y ago

Finally, we can build a robot that can play a game of peepo :)