Recent content by spacemax

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

The point about testing and debugging 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. It also gives you a cleaner baseline if you want to compare tools or settings later.

For Model Training & Fine-Tuning, it helps to think in terms of inputs, constraints, verification, and iteration. One important area is useful tools. 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...