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!
If you keep Dropout at Inference time, you don’t get deterministic results, even if the input stays constant. People sometimes think you can use this to derive uncertainty (I don’t).