I’ve been interested in AI since school, coming from my video gaming hobby. Neural nets have always piqued my interest, so I decided that I will jump in to this and learn through both doing and researching. I’m starting, intentionally without doing any research, by giving building a basic neural net a shot. I think it could be interesting to document my growth, and see how things evolve as I learn more. The first repo I have to share my work is https://github.com/silasray/aiexplore . I intend to spend at least a few hours a day on this for the foreseeable future, so let’s see how it goes, and with some luck, it’ll be an interesting look into learning.

The initial code in the repo is just a start, not running. I’m trying to build a simple neural network, where there will be a solve phase and a reinforce phase. Solve will take inputs and produce an output, and reinforce will modify the network to “learn”. Right now, basically, the idea is that the training resides in the Synapses (aka edge weights) while the solving is localized in the Neurons. I’m sure this is incredibly novice, but that’s kind of the point. I’m excited to see where it goes.