Building on our recent article about the potential of AI workers, we look at examples of the evolution from conventional methods to AI-driven processes in regulated fields such as Information Security, Law, and Finance.
Traditionally, developers have been firmly in charge of engineering prompts within AI applications. This crucial task, which involves crafting the queries and commands that guide AI responses, has required a deep understanding of coding and a nuanced grasp of the AI's operating framework.
Every development in AI promises new peaks of potential, and one discipline continues to evolve for harnessing these heights—prompt engineering. Prompt engineering is a field where precise phrasing guides Large Language Models (LLMs) like ChatGPT to produce astonishingly useful responses.
The AI revolution, marked by the ascension of Generative AI and Large Language Models (LLMs), has crystallized a profound shift in business strategy. Yet, amidst the pulsating hype, the purview of LLMOps will winnow out fleeting endeavors from lasting innovations.
AI has been a pioneering force, challenging our preconceptions and pushing the boundaries of what machines can achieve. Our interactions with these algorithmic entities, particularly with models such as Generative Pre-trained Transformers (GPTs), reveal deep truths about AI and ourselves.
