Recent content by poppycloud40

A useful way to understand AI Troubleshooting is to separate the goal, the input, the model or tool, and the way the output is evaluated. One important area is automation. Define what a good result looks like before changing tools or settings, then test one variable at a time so you can tell...

I think privacy and data 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.