I had a discussion in class with one of my teachers. He says that AI is and can only be always deterministic because “even a deep learning neural network is a set of equations running on a computer, and the stochastic factor is added at the beginning. But the output of a model is always deterministic, even if it’s not interpretable by humans.”
How would you reply? (Possibly with examples and papers)
Tysm!
A single AI network is deterministic. If you apply the same input, you get the same output. If you train on the same dataset, in the same order, with the same initial weights and hyperparameters, you will get an identical training result.
The tricky thing is that AI is high dimensional and non-linear. So what appears to be a very small change to the input can cause a large change in the output. I think the clearest example of this is adversarial AI.
It also has to be the same hardware…