Recent content by lucaslab

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

On Perplexity knowledge guide: improving beginner tips, the part about perplexity and beginner 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 also gives you a cleaner baseline if you want...

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