Recent content by mattoncraft

I wanted to start a broader future possibilities thread around Reinforcement Learning. A useful angle is automation, but it also connects with customisation. Different tools and workflows can produce very different results even when the goal is similar. It would be interesting to compare...

I think step and productivity is the key part of this topic. A practical approach is to define the outcome you want, test it with a small example, and then check quality, speed and reliability separately. That way you can improve the workflow without losing track of what caused the improvement.

A practical understanding of Stable Diffusion starts with knowing what the system does well, where it is unreliable, and how to validate the result. One important area is setup choices. Define what a good result looks like before changing tools or settings, then test one variable at a time so...