Seriously... The ability to identify what physics/math theories the AI should apply and being able to make the AI actually apply those are very different things. And you don't seem to understand that distinction.
Unless you have $500k to pay for the actual implementation of a Hamiltonian video generator then I don't think you're in a position to tell me what I know and don't know.
lolz, I doubt very much anyone would want to pay you $500k to perform magic. Basically, I think you are coming across as someone who is trying to sound clever rather than being clever.
My price is very cheap in terms of what it would enable and allow OpenAI to charge their customers. Hamiltonian video generation with conservation principles which do not have phantom masses appearing and disappearing out of nowhere is a billion dollar industry so my asking price is basically giving away the entire industry for free.
Sure, but I imagine the reason you haven't started your own company to do it is you need 10s of millions in compute, so the price would be 500k + 10s of millions... Or you can't actually do it and are just talking shit on the internet.
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?