Recent content by aiden_1gha

For Make, it helps to think in terms of inputs, constraints, verification, and iteration. One important area is deployment. 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. Another area...

For What is the best way to approach data quality for Large Language Models?, I would separate the problem into setup, output quality and repeatability. data and quality fits into that because it can change the result quite a lot depending on the workflow. The original point — "I have been...

When working with AI Game Animation, the biggest gains usually come from treating it as a repeatable workflow rather than a one-off prompt or experiment. One important area is limitations. Define what a good result looks like before changing tools or settings, then test one variable at a time...