good luck reverse-engineering millions if not billions of seemingly random floating point numbers. It’s like visualizing a graph in your mind by reading an array of numbers, except in this case the graph has as many dimensions as the neural network has inputs, which is the number of pixels the input image has.
Under no circumstance should we accept a “black box” explanation.
Go learn at least basic principles of neural networks, because this your sentence alone makes me want to slap you.
Don’t worry, researchers will just get an AI to interpret all those floating point numbers and come up with a human-readable explanation! What could go wrong? /s
good luck reverse-engineering millions if not billions of seemingly random floating point numbers. It’s like visualizing a graph in your mind by reading an array of numbers, except in this case the graph has as many dimensions as the neural network has inputs, which is the number of pixels the input image has.
Go learn at least basic principles of neural networks, because this your sentence alone makes me want to slap you.
Don’t worry, researchers will just get an AI to interpret all those floating point numbers and come up with a human-readable explanation! What could go wrong? /s