Recent content by road_isla

For llama.cpp, it helps to think in terms of inputs, constraints, verification, and iteration. One important area is collaboration. 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...

The point about data and quality 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 AI Voice Generation, it helps to think in terms of inputs, constraints, verification, and iteration. One important area is real-world use. 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...