What is Prompt Engineering?

How LLMs work

What is an LLM:

 A Large Language Model (LLM) is a type of artificial intelligence (AI) model designed to understand and generate human language at a high level. LLMs are built on neural network architectures, particularly deep learning models, and are trained on vast datasets that include text from books, websites, research papers, and other language-rich sources.

The purpose of these models is to perform tasks that involve natural language processing (NLP). Examples of LLMs include OpenAi's ChatGPT and Microsoft Copilot.

How LLMs work:

An LLM works by using transformer-based models used in natural language processing (NLP). These models have revolutionized NLP tasks by leveraging the transformer architecture, which is highly effective for tasks like language generation, translation, question answering, and more. 

BERT (Bidirectional Encoder Representations from Transformers): BERT is a model designed to understand the context of words in a sentence by looking at the words before and after a target word. It excels at tasks like sentence classification and named entity recognition.

GPT (Generative Pre-trained Transformer): GPT is primarily focused on language generation. It uses a unidirectional approach, generating coherent text based on a given prompt. GPT models like GPT-3 and GPT-4 are widely used in conversational AI and text completion.

T5 (Text-to-Text Transfer Transformer): T5 is a model that treats every NLP task as a text-to-text problem, whether it's translation, summarization, or question answering. It can take in text and generate a corresponding output in a text format.

Why It Matters

In today’s AI-driven economy, the quality of an AI’s output depends on the quality of the input. Employees who master prompt engineering can unlock the full potential of AI tools, driving efficiency, improving decision-making, and enhancing customer experiences.