What Can Large Language Models (LLMs) Be Used For?

Large language models (LLMs) are complex algorithms that have learned from massive amounts of data using the Transformer architecture pioneered by Google researchers six years ago. These models can process and understand text data almost as well as a human brain, but much faster, making them suitable candidates for various text-based tasks across industries such as copywriting and editing, customer support, automated text summarization, translation, information extraction, programming, and more. LLMs are created by training on vast amounts of data using massive computing resources and fine-tuning techniques, allowing them to be shared and reused endlessly. While they can replace humans in certain tasks, a human-in-the-loop approach is recommended to ensure the quality of their output. Strategies for harnessing the power of LLMs include retrieval augmentation generation (RAG), prompt engineering, fine-tuning, and using centralized platforms like deepset Cloud to expedite building industry applications with LLMs. By understanding how to work with LLMs effectively, developers can significantly speed up their work process and increase productivity.