Recent content by henryonmountain

For Deep Learning, it helps to think in terms of inputs, constraints, verification, and iteration. 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 improved the outcome. Another...

I think security and news is the key part of this topic. A practical approach is to define the outcome you want, test it with a small example, and then check quality, speed and reliability separately. That should make it easier to tell whether the change is actually helping.

For AI Advertising, it helps to think in terms of inputs, constraints, verification, and iteration. One important area is security. 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...