I was going to ask the same thing. It may not be possible to create a simple vector representation of the circuit if the circuit must simulate a complex nonlinear system. Doesn’t seem possible, if the inputs are embeddings or sensor data from real world causal dynamic systems like images and text; and the outputs are vector space representations of the meaning in the inputs (semantic segmentation, NLP, etc). If it were possible it’s like saying there’s a simple, consitent vector representation of all the common sense reasoning about a particular image or natural language text. And your rotated explainable embedding would be far more accurate and robust than the original spaghetti circuit/program. Some programs are irreducible.
I think the best you can do is something like Capsule Nets (Hinton) which are many of your rotations (just smaller, 4 d quaternions, I think) distributed throughout the circuit.
I was going to ask the same thing. It may not be possible to create a simple vector representation of the circuit if the circuit must simulate a complex nonlinear system. Doesn’t seem possible, if the inputs are embeddings or sensor data from real world causal dynamic systems like images and text; and the outputs are vector space representations of the meaning in the inputs (semantic segmentation, NLP, etc). If it were possible it’s like saying there’s a simple, consitent vector representation of all the common sense reasoning about a particular image or natural language text. And your rotated explainable embedding would be far more accurate and robust than the original spaghetti circuit/program. Some programs are irreducible.
I think the best you can do is something like Capsule Nets (Hinton) which are many of your rotations (just smaller, 4 d quaternions, I think) distributed throughout the circuit.