Absolutely, let’s get into it. First, we need to make the network transparent—add explainable layers or attention maps so you can see why it’s making a decision. Next, enforce a fairness loss so it doesn’t bias toward any road type. And sprinkle in some regularization to keep it from over‑fitting to a single track. With those tweaks, the bike will stay honest and free to learn from the road.

Yeah, let’s fire it up and see how the AI rides with the real world—no shortcuts, just raw learning. Let's do this.