Recent content by oscarspark

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

On AI Smart Glasses knowledge guide: improving real-world use, the part about smart and glasses stands out to me. I would test one small workflow first, keep the variables consistent, and compare the result before changing several things at once. It is usually easier to troubleshoot when each...

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