Introduction
What is "Prompt Engineering" ?
To understnd, pay attention on the Green highlighted words
Prompt engineering is the process of designing and refining prompts to guide the behavior of large language models (LLMs) and other generative AI tools to elicit the desired output from the model. It is an iterative process of experimenting with different prompts to see how they affect the model's output, and then using that knowledge to refine the prompts further.
What is "LLM" ?
Large Language Models (LLMs) are a subclass of Artificial Intelligence (AI) adept at understanding and generating human language. Their monumental size, often characterized by billions of parameters, empowers them to learn intricate relationships between words and concepts, leading to a wider range of capabilities compared to traditional language models.
Key characteristics of LLMs:
Scalability: Their massive parameter count enables them to tackle complex tasks with higher accuracy and nuance.
Versatility: LLMs handle diverse language-related tasks, including:
Text Generation: Producing different text formats like poems, code, scripts, musical pieces, and various communication forms.
Text Comprehension: Analyzing text to understand its meaning, answer questions, and provide summaries.
Translation: Efficiently translating text between languages.
Dialogue: Engaging in human-like conversations and responding to prompts in a conversational manner.
Training: LLMs undergo rigorous training on vast text datasets using self-supervised and semi-supervised learning techniques.
Examples: Prominent LLM examples include Gemini, GPT-4, LLaMA, Phi-2 etc..