Recent content by brain_laura

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

For AI Startups knowledge guide: improving common mistakes, I would separate the problem into setup, output quality and repeatability. startups and common fits into that because it can change the result quite a lot depending on the workflow. It is usually easier to troubleshoot when each change...

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