Introduction to Computers - Lecture 7

These flashcards cover key concepts from the lecture on Generative AI, LLMs, and their applications in automation and prompt engineering.

Generative AI

A type of artificial intelligence that creates new content such as text, images, audio, and video by learning patterns from large datasets.

Training

The process by which generative AI models learn underlying patterns and structures from massive datasets.

Pattern Recognition

The ability of the model to analyze data and recognize complex patterns and relationships between different elements.

ChatGPT

A chat interface for a Generative Pre-trained Transformer (GPT) machine learning model that generates believable text.

LLM (Large Language Model)

A text-based machine learning model that is trained on vast amounts of text to learn relationships between words.

Hallucinations in LLMs

Instances when AI models like ChatGPT make up information that is completely incorrect.

Prompt Engineering

The process of designing and refining input prompts given to LLMs to elicit accurate and useful responses.

Zero Shot Prompt

A type of prompt where only the task description is provided to the model without any examples or guidance.

One-Shot and Few-Shot Prompt

One-shot prompting provides a single example, while few-shot prompting gives multiple examples to guide the model.

Automation

The process of enabling systems to carry out tasks independently, without continuous human oversight.

AI-powered Chatbots

Intelligent systems that provide customer service support by responding to FAQs and handling queries.

Content Generation

The ability of generative AI to create new content in response to prompts, such as text, images, or audio.

Customer Service Automation

Systems that reduce the workload on human agents by providing 24/7 support through AI.

Language Translation

The use of AI tools to translate content in real-time, enabling communication across different languages.