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AI is always deterministic. We add noise to the models to get "non-deterministic" results, but if the noise and input is the same, the output is also the same.
by leoff 3y ago
AI is always deterministic. We add noise to the models to get "non-deterministic" results, but if the noise and input is the same, the output is also the same.
- david-gpu 3y agoIt's a bit more nuanced than that. Floating point arithmetic is not associative: "(A+B)+C" is not always equal to "A+(B+C)". Because of that, certain mathematical operations used in neural networks, such as parallel reductions, will yield slightly different results if you run them multiple times with the same arguments. There are some people working hard to provide the means to perform deterministic AI computations like these, but that will come with some performance losses, so I would guess that most AIs will continue to be (slightly) non-deterministic.
- nuancebydefault 3y agoIs AI in general relying on floating point calculations?
- david-gpu 3y agoOne hundred percent. It's mostly fancy floating point matrix multiplications.
- Rygian 3y agoThat assumes an AI that is trained exactly once ever.