I would love to see some work on duality i.e. code to neural network back and forth. Reason being - I can't debug a neural network but if it can be linearized into a if-else case with help of the token information => I can validate what it's doing -> fix it and then move it back to it's compressed neural representation.
Just another thought experiment -> sometimes I imagine neural networks as a zip of the training data where compression algorithm is backpropagation. Just like we have programs which let us see what files inside the zip are -> I imagine there can be programs which will let us select certain inference path of the neural net and then see what data affected that => then we edit that data to fix our issues or add more data there => and we have live neural network debugging and reprogramming in the same way we edit compressed zips
Just another thought experiment -> sometimes I imagine neural networks as a zip of the training data where compression algorithm is backpropagation. Just like we have programs which let us see what files inside the zip are -> I imagine there can be programs which will let us select certain inference path of the neural net and then see what data affected that => then we edit that data to fix our issues or add more data there => and we have live neural network debugging and reprogramming in the same way we edit compressed zips