I do not agree that neural networks are a "black box" with "no ability to inspect and verify". Even putting aside the many methods to understand what a neural network is doing without running it, at core, neural networks are well tested instruments. That's how they learn-- by testing themselves.
Obviously it's possible for a neural network to have odd behavior in circumstances not accounted for but that was always going to be possible at the level of complexity we're talking about here.
We're talking about cutting edge technology here -- and I agree with your general sentiment. I just don't agree with pinning the blame on "... based on neural networks". The same factors would apply to any codebase of this complexity.
I had the same problem until a recent TS release introducing the keyof feature. You can create a TypeScript type that automatically convert a class definition to stubs.
type StubInstance<T> = {
[P in keyof T]: sinon.SinonStub;
};
I do not agree that neural networks are a "black box" with "no ability to inspect and verify". Even putting aside the many methods to understand what a neural network is doing without running it, at core, neural networks are well tested instruments. That's how they learn-- by testing themselves.
Obviously it's possible for a neural network to have odd behavior in circumstances not accounted for but that was always going to be possible at the level of complexity we're talking about here.
We're talking about cutting edge technology here -- and I agree with your general sentiment. I just don't agree with pinning the blame on "... based on neural networks". The same factors would apply to any codebase of this complexity.