Recent content by runner_millie

For Deep Learning, it helps to think in terms of inputs, constraints, verification, and iteration. One important area is accessibility. 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...

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