Technology

AI is a magical black box that performs a bunch of actions to produce an output. We can’t trust what a developer says the black box does inside without it being completely open source (including weights).

This is a concept for a system where the actions performed can be proved to those who don’t have visibility inside the box to trust the box is doing what it is saying it’s doing.

An AI enemy that can prove it isn’t cheating by providing proof of the actions it took. In theory.

Zero Knowledge Proofs make a lot of sense for cryptography but in a more abstracted sense like this, it still relies on a lot of trust that the implementation generates proofs for all actions.

Whenever I see Web3, I personally lose any faith in whatever is being presented or proposed. To me, blockchain is an impressive solution to no real problem (except perhaps border control / customs).

The way AI is trained today creates a black box solution, the author says only the developers of the model know what goes on inside the black box.

This is major pain point in AI, where we are trying to understand it so we can make it better and more reliable. The author mentions that unless AI companies open source their work, it's impossible for everyone else to 'debug' the circuit.

Zero knowledge proofs are how they are trying to combat this, using mathematical algorithms they are trying to verify the output of an AI model in real time, without having to know the underlying intellectual property.

This could be used to train AI further and increase the reliability of AI drastically, so it could be used to make more important decisions and adhere much more easily to the strategies for which they are deployed.