Letting neural networks be weird
aiweirdness.com
Letting neural networks be weird
1–10 of 27 posts
Re: Letting neural networks be weird
#2In my opinion, it is very, very hard to fully sandbox a clever AI. It can find side channels, or it can turn innocuous stuff into computing device...
e.g: "Accidentally Turing complete" shows how things that were not intended to be computing devices are actually Turing complete. Including: Magic the gathering, the card game.
http://beza1e1.tuxen.de/articles/accidentally_turing_complet...
Re: Letting neural networks be weird
#3In my opinion, it is very, very hard to fully sandbox a clever AI. It can find side channels, or it can turn innocuous stuff into computing device... e.g: "Accidentally Turing complete" shows how things that were not intended to be computing devices are actually Turing complete. Including: Magic the gathering, the card game. http://beza1e1.tuxen.de/articles/accidentally_turing_complet...
I've often thought that JIRA workflows are Turing complete, I was hoping your list would have evidence.
Re: Letting neural networks be weird
#4It's interesting that so much neural net weirdness emerges from exploiting errors in physics simulators or floating point math.
I am now expecting the next generation of perpetual motion machines to include AI to try to take advantage of physics bugs in our own universe.
On a related note, does anyone know how you might go about fixing a simulator that allows collisions to generate more energy/momentum than was initially supplied? Or otherwise violates known invariants?
Re: Letting neural networks be weird
#5Bad title (in the original) because the examples in the paper are mostly drawn evolutionary computation and artificial life, with only a few relating to neural networks being used in those fields.
Re: Letting neural networks be weird
#6In my opinion, it is very, very hard to fully sandbox a clever AI. It can find side channels, or it can turn innocuous stuff into computing device... e.g: "Accidentally Turing complete" shows how things that were not intended to be computing devices are actually Turing complete. Including: Magic the gathering, the card game. http://beza1e1.tuxen.de/articles/accidentally_turing_complet...
I've often thought that JIRA workflows are Turing complete, I was hoping your list would have evidence.
It’s funny to think of JIRA as Turing complete because when using JIRA nobody can complete any programs.
Re: Letting neural networks be weird
#7In my opinion, it is very, very hard to fully sandbox a clever AI. It can find side channels, or it can turn innocuous stuff into computing device... e.g: "Accidentally Turing complete" shows how things that were not intended to be computing devices are actually Turing complete. Including: Magic the gathering, the card game. http://beza1e1.tuxen.de/articles/accidentally_turing_complet...
I've often thought that JIRA workflows are Turing complete, I was hoping your list would have evidence.
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Re: Letting neural networks be weird
#8It's interesting that so much neural net weirdness emerges from exploiting errors in physics simulators or floating point math. I am now expecting the next generation of perpetual motion machines to include AI to try to take advantage of physics bugs in our own universe. On a related note, does anyone know how you might go about fixing a simulator that allows collisions to generate more energy/momentum than was initi…
Would TVD help?
https://en.wikipedia.org/wiki/Total_variation_diminishing
Re: Letting neural networks be weird
#9Earlier quoted context omitted.
I've often thought that JIRA workflows are Turing complete, I was hoping your list would have evidence.
It’s funny to think of JIRA as Turing complete because when using JIRA nobody can complete any programs.
Well, everything halts then, so that just solved the Halting Problem.
Re: Letting neural networks be weird
#10It's interesting that so much neural net weirdness emerges from exploiting errors in physics simulators or floating point math. I am now expecting the next generation of perpetual motion machines to include AI to try to take advantage of physics bugs in our own universe. On a related note, does anyone know how you might go about fixing a simulator that allows collisions to generate more energy/momentum than was initi…
You want a symplectic integrator (https://en.m.wikipedia.org/wiki/Symplectic_integrator) such as Verlet Integration (https://en.m.wikipedia.org/wiki/Verlet_integration). Such integrators naturally conserve energy and momentum as long as your forces and energies are self-consistent and you don't use gigantic timesteps.
A classic mistake is to use something like "velocity += acceleration*time" (this is called Euler integration). It looks reasonable, and it's good enough for a toy project, but it doesn't conserve energy unless the timesteps are infinitely small.
A more sophisticated mistake is to use something like Runge-Kutta Integration: highly accurate in terms of position, but it is not symplectic so the total energy will drift over time. Think of your simulated world as a stack of graph paper sheets, where each sheet represents a surface of constant energy. Runge-Kutta will take you very close to the ideal (x,y) point - but not necessarily on the same sheet. Verlet Integration may be a little further from the right point each time, but by its mathematical form it will always stay on the same sheet.