New Prompt Engineering Technique Pumps-Up
– Prompt engineering, also known as prompt design, is vital for effectively using generative AI and improving results.
– Chain-of-thought (CoT) reasoning is a technique where generative AI explains its logic step-by-step to produce more reliable and on-target answers.
– Factored decomposition is an added technique that uplifts CoT reasoning to a higher level of capability and results in more faithful reasoning.
– When using CoT, the generative AI may not necessarily showcase the true step-by-step actions, but the steps provided can still be useful and beneficial.
– Instructing the AI to use chain-of-thought can improve the reliability and correctness of generated answers, possibly due to exploring more avenues within the AI's neural network.
– Decomposition, as an added technique for CoT, involves instructing the AI to generate a series of subquestions and sub-answers, potentially further enhancing the CoT effort.
– Factored decomposition, a variation of decomposition, prompts the AI to stop at each subquestion and start a fresh conversation, possibly leading to more reliable answers and more faithful reasoning.
– Research studies are examining the effectiveness of chain-of-thought augmented by decomposition, focusing on the faithfulness of model-generated reasoning.
– The goal is to determine whether the AI's elucidation of steps and reasoning faithfully represents how it arrived at the generated answers, as opposed to being contrived and disconnected from the internal processes.