In the previous post, I made an introduction and a POC to interact with ONNX models and Go. I have decoded the information to reconstruct a graph. Now I propose to expand the principle and to create a proper execution backend based on Gorgonia. This post is a bit more technical than the previous one because all the concepts needed to work should be present in the last article.

This year has started with a lot of deep thoughts about the software 2.0. My conclusion (which is slightly different from Andrej Karpathy’s consideration) is that a software 2.0 is a combination of a Neural network model and its associated weights. This is a concept; now the question is: how to materialize the idea? What artifact represents a software 2.0. I emitted several ideas and tried one of them: to serialize the mathematical model and the weights.