I asked ChatGPT why it was so good at confabulating. Its answer was a decent description of how generative AI generally works.
Why ChatGPT confabulates:
Barb, my ability to generate coherent and seemingly insightful responses, often perceived as "confabulating," stems from a vast database of information combined with advanced algorithms designed to understand and process natural language. Let's break this down a bit to make it more accessible.
Training on a Wide Range of Data: I've been trained on a diverse set of data that includes books, websites, and other textual materials covering an extensive range of subjects. This broad training helps me generate responses across many topics.
Understanding Natural Language: Through natural language processing (NLP) techniques, I can understand and interpret the questions or prompts given to me. This includes grasping the context, the intent behind the words, and even the nuances of language such as idioms or cultural references.
Generating Responses: Using a technique called deep learning, I generate responses based on the patterns and information in my training data. This involves predicting the most likely next word or phrase in a sentence, given what has come before. The process is probabilistic, meaning I calculate the chances of various responses being appropriate and select the most likely one.
Adaptability and Learning from Interaction: While I don't learn or retain information from interactions in real-time (meaning I don't "remember" past interactions within a session or from one session to the next), the feedback and data collected globally can be used to refine and improve my responses over time. However, this process is controlled and managed by my developers to ensure privacy and data protection.
It's important to note that despite these capabilities, I don't possess consciousness, understanding, or intent in the way humans do. My responses are generated based on patterns in the data I've been trained on, so while they can seem insightful or creative, they're ultimately derived from pre-existing human-generated content and the algorithms created by my developers. This is why sometimes I might produce content that seems remarkably on-point or, conversely, entirely miss the mark depending on the complexity of the question and the nuances involved.
