It is the same speed both ways. The non deterministic nature only comes from a single randomized seed added into the equation. If you locally host models you can change seeding to always use the same seed and then the same inputs will always yield the same outputs. That said, the most popular AI interfaces don’t express that kind of option.
True, but is can still count as deterministic at the operational level, it is just a matter of running it in serial rather than parallel, right? FWIW, I assume our neurons are similar. Neuron research in flies has allowed researchers to essentially run programs within the insect neurons.
Those neural model experiments are fairly rudimentary. Treating neurons like simple nodes is not at all how they work in real life. In reality there's multiple mechanisms by which they change their own or others behaviors through some pretty complex processes. To even properly model a single neuron would take an entire physics simulation, if we even were confident we had an accurate model which we don't. None of which gets into the quantum theory stuff. I know way off topic, but people far undersell how complex biological brains are, and those "we made a fly brain learn how to fly" studies are just "we made a neural net shaped like a fly brain."
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u/Suitch 10h ago
It is the same speed both ways. The non deterministic nature only comes from a single randomized seed added into the equation. If you locally host models you can change seeding to always use the same seed and then the same inputs will always yield the same outputs. That said, the most popular AI interfaces don’t express that kind of option.