LLMs aren’t perfect. In fact, that’s how they’re meant to be. LLMs are probabilistic systems. They work by providing different possible results based on what the inputs could probably mean and based on what data is probably relevant. Given all those possibilities and probabilities, LLMs are bound to get things wrong. In this episode hosts Kathleen Walch and Ron Schmelzer discuss using custom instructions for LLMs and why this is a best practice.
Continue reading Prompt Engineering Best Practices: Using Custom Instructions [AI Today Podcast] at Cognilytica.