In this talk, we'll walk through how to make large language models more truthful and thus trustworthy at an enterprise scale using few or zero-shot approaches with a vector database, context injection, prompt chaining, and transfer learning.
Why? Because large language models lack deductive reasoning or a cognitive architecture, which makes them epistemologically blind to what they know they know and their known unknowns. This makes them unreliable even with fine-tuning approaches alone.