Recent content by captainlaura

A useful way to understand Google Veo is to separate the goal, the input, the model or tool, and the way the output is evaluated. One important area is testing. 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...

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