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What are the differences between generative AI vs. large language models? How are these two buzzworthy technologies related? In this article, we’ll explore their connection. To help explain the concept, I asked ChatGPT to give me some analogies comparing generative AI to large language models (LLMs), and as the stand-in for generative AI, ChatGPT tried to take all the personality for itself.

Maya Angelou once said, “You are the sum total of everything you’ve ever seen, heard, eaten, smelled, been told, forgot—it’s all there. Everything influences each of us, and because of that I try to make sure that my experiences are positive.” Experiences matter. They matter to us in our personal lives but also in our work lives as employees, customers, and software users. That’s why total experience is such an effective business strategy.

With the emergence of new creative AI algorithms like large language models (LLM) fromOpenAI’s ChatGPT, Google’s Bard, Meta’s LLaMa, and Bloomberg’s BloombergGPT—awareness, interest and adoption of AI use cases across industries is at an all time high. But in highly regulated industries where these technologies may be prohibited, the focus is less on off the shelf generative AI, and more on the relationship between their data and how AI can transform their business.