Recent content by jamesrid

A practical understanding of General AI Image Generation starts with knowing what the system does well, where it is unreliable, and how to validate the result. One important area is customisation. Define what a good result looks like before changing tools or settings, then test one variable at...

The point about mistakes and common is interesting. In practice I would keep the first test simple, record what worked, and only add extra complexity if it solves a specific limitation. That way you can improve the workflow without losing track of what caused the improvement.

For AI 3D Models, it helps to think in terms of inputs, constraints, verification, and iteration. One important area is reliability. Define what a good result looks like before changing tools or settings, then test one variable at a time so you can tell what actually improved the outcome...