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Neural networks use smooth manifolds as their underlying inductive bias so in theory it should be possible to incorporate smooth kinematic and Hamiltonian const
by benchmarkist 2y ago
Neural networks use smooth manifolds as their underlying inductive bias so in theory it should be possible to incorporate smooth kinematic and Hamiltonian constraints but I am certain no one at OpenAI actually understands enough of the theory to figure out how to do that.
- david-gpu 2y ago> I am certain no one at OpenAI actually understands enough of the theory to figure out how to do that We would love to learn more about the origin of your certainty.
- benchmarkist 2y agoI don't work there so I'm certain there is no one with enough knowledge to make it work with Hamiltonian constraints because the idea is very obvious but they haven't done it because they don't have the wherewithal to do so. In other words, no one at OpenAI understands enough basic physics to incorporate conservation principles into the generative network so that objects with random masses don't appear and disappear on the "video" manifold as it evolves in time.
- david-gpu 2y ago> the idea is very obvious but they haven't done it because they don't have the wherewithal to do so Fascinating! I wish I had the knowledge and wherewithal to do that and become rich instead of wasting my time on HN.
- benchmarkist 2y agoNo one is perfect but you should try to do better and waste less time on HN now that you're aware and can act on that knowledge.
- david-gpu 2y agoNah, I'm good. HN can be a very amusing place at times. Thanks, though.
- dartos 2y agoHow does your conclusion follow from your statement? Neural networks are largely black box piles of linear algebra which are massaged to minimize a loss function. How would you incorporate smooth kinematic motion in such an environment? The fact that you discount the knowledge of literally every single employee at OpenAI is a big signal that you have no idea what you’re talking about. I don’t even really like OpenAI and I can see that.
- benchmarkist 2y agoI've seen the quality of OpenAI engineers on Twitter and it's easy enough to extrapolate. Moreoever, neural networks are not black boxes, you're just parroting whatever you've heard on social media. The underlying theory is very simple.
- dartos 2y agoDo not make assumptions about people you do not know in an attempt to discredit them. You seem to be a big fan of that. I have been working with NLP and neural networks since 2017. They aren’t just black boxes, they are _largely_ black boxes. When training an NN, you don’t have great control over what parts of the model does what or how. Now instead of trying to discredit me, would you mind answering my question? Especially since, as you say, the theory is so simple. How would you incorporate smooth kinematic motion in such an environment?
- benchmarkist 2y agoWhy would I give away the idea for free? How much do you want to pay for the implementation?
- dartos 2y agolol. Ok dude you have a good one.
- benchmarkist 2y ago
- esafak 2y agoThere are physicists at OpenAI. You can verify with a quick search. So someone there clearly knows these things.
- benchmarkist 2y agoI'd be embarrassed if I was a physicists and my name was associated with software that had phantom masses appearing and disappearing into the void.
- esafak 2y agoWhy don't you write a paper or start a company to show them the right way to do it?
- benchmarkist 2y agoI don't think there is any real value in making videos other than useless entertainment. The real inspired use of computation and AI is to cure cancer, that would be the right way to show the world that this technology is worthwhile and useful. The techniques involved would be the same because one would need to include real physical constraints like conservation of mass and energy instead of figuring out the best way to flash lights on the screen with no regard for any foundational physical principles. Do you know anyone or any companies working on that?