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Below, I have collected a few explanations of terms that are cropping up relating to AI. This list will of course be a work in progress, and will continue to be expanded and revised.
If there are any terms you think should be included, please send me a note through the support link in the menu above.
AI - Artificial Intelligence
AI, or Artificial Intelligence, refers to computer systems designed to mimic human intelligence. These systems learn from data and experiences, enabling them to perform tasks like problem-solving, pattern recognition, and decision-making. AI powers various technologies, from voice assistants to self-driving cars, transforming how machines interact and assist in our everyday life.
An algorithm is a set of step-by-step instructions for solving a problem or completing a task. It's like a recipe that guides computers to perform specific actions, process data, or make decisions. Algorithms underpin various digital processes, from search engines to data analysis, shaping how technology works.
A chatbot is a computer program that chats with people using text or speech. It uses AI to understand and respond to human queries, providing information, assistance, or entertainment. Chatbots are employed in customer service, information retrieval, and interactive experiences, simulating conversations and enhancing user engagement.
DRL - Deep Reinforcement Learning
Deep reinforcement learning is an AI technique where an algorithm learns how to make decisions by interacting with an environment. It uses deep neural networks to understand patterns and optimize actions, receiving rewards for good decisions. This approach is used in training agents for tasks like gaming, robotics, and autonomous systems.
LLM - Large Language Model
A large language model is a sophisticated AI system designed to understand and generate human-like text. By learning from vast amounts of text data, it can perform tasks like answering questions, creating content, and engaging in conversations with users, mimicking human language patterns and knowledge across various subjects.
A neural network is a computer system modeled after the human brain's interconnected neurons. It processes information by learning patterns from data, enabling it to recognize complex relationships and make predictions. Neural networks are key components of AI, used in tasks like image recognition, language processing, and decision-making.
Ever used a search query to get specific results? An AI prompt is similar—it's a simple instruction or question you give to an AI to get useful outputs. It guides the AI in producing tailored responses or content, making your interaction more productive and personalized.
Prompts are the backbone of working with AI content generators. It is also the most important thing to keep educating yourself about. With great prompts even a mediocre AI can produce good results. With bad prompts, even the best AI will produce mediocre results.
Prompt engineering involves crafting effective instructions or queries to guide AI models. By fine-tuning prompts, wording, and parameters, it enhances AI's responses and output quality. This iterative process optimizes communication between users and AI, ensuring accurate, tailored results and enabling versatile applications across diverse tasks.